End of training
Browse files- README.md +98 -0
- adapter_config.json +37 -0
- adapter_model.safetensors +3 -0
- all_results.json +12 -0
- special_tokens_map.json +107 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +939 -0
- train_results.json +12 -0
- trainer_state.json +2401 -0
- training_args.bin +3 -0
README.md
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| 1 |
+
---
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library_name: peft
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license: apache-2.0
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+
base_model: google-t5/t5-base
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tags:
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- base_model:adapter:google-t5/t5-base
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- lora
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- transformers
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| 9 |
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datasets:
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- Andyrasika/TweetSumm-tuned
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metrics:
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- rouge
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- f1
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| 14 |
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- precision
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- recall
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model-index:
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- name: t5-base-lora-finetune-tweetsumm-1759927258
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results:
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- task:
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type: summarization
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name: Summarization
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dataset:
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name: Andyrasika/TweetSumm-tuned
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type: Andyrasika/TweetSumm-tuned
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metrics:
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- type: rouge
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value: 0.4479
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name: Rouge1
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- type: f1
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value: 0.8903
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| 31 |
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name: F1
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- type: precision
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value: 0.8875
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name: Precision
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- type: recall
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value: 0.8934
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name: Recall
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# t5-base-lora-finetune-tweetsumm-1759927258
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the Andyrasika/TweetSumm-tuned dataset.
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+
It achieves the following results on the evaluation set:
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- Loss: 1.8236
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- Rouge1: 0.4479
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- Rouge2: 0.2102
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- Rougel: 0.3774
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- Rougelsum: 0.415
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| 52 |
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- Gen Len: 46.3273
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| 53 |
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- F1: 0.8903
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| 54 |
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- Precision: 0.8875
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| 55 |
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- Recall: 0.8934
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| 56 |
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## Model description
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More information needed
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## Intended uses & limitations
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| 62 |
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More information needed
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| 64 |
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| 65 |
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## Training and evaluation data
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| 66 |
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| 67 |
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More information needed
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| 68 |
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| 69 |
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## Training procedure
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| 70 |
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| 71 |
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### Training hyperparameters
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| 72 |
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| 73 |
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The following hyperparameters were used during training:
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| 74 |
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- learning_rate: 0.001
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| 75 |
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- train_batch_size: 8
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| 76 |
+
- eval_batch_size: 8
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| 77 |
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- seed: 42
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| 78 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| 79 |
+
- lr_scheduler_type: linear
|
| 80 |
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- num_epochs: 3
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| 81 |
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- mixed_precision_training: Native AMP
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| 82 |
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|
| 83 |
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### Training results
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| 84 |
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|
| 85 |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | F1 | Precision | Recall |
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| 86 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:---------:|:------:|
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| 87 |
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| 2.106 | 1.0 | 110 | 1.8968 | 0.44 | 0.2049 | 0.3691 | 0.4078 | 49.3455 | 0.8867 | 0.8832 | 0.8904 |
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| 88 |
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| 1.8113 | 2.0 | 220 | 1.8425 | 0.4405 | 0.2078 | 0.3706 | 0.4044 | 47.9455 | 0.8895 | 0.887 | 0.8921 |
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| 89 |
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| 1.5495 | 3.0 | 330 | 1.8236 | 0.4479 | 0.2102 | 0.3774 | 0.415 | 46.3273 | 0.8903 | 0.8875 | 0.8934 |
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| 90 |
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| 91 |
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| 92 |
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### Framework versions
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| 93 |
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| 94 |
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- PEFT 0.17.1
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| 95 |
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- Transformers 4.56.2
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| 96 |
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- Pytorch 2.8.0+cu126
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| 97 |
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- Datasets 4.0.0
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| 98 |
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- Tokenizers 0.22.1
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adapter_config.json
ADDED
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{
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| 2 |
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"alpha_pattern": {},
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| 3 |
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"auto_mapping": null,
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| 4 |
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"base_model_name_or_path": "google-t5/t5-base",
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| 5 |
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"bias": "none",
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| 6 |
+
"corda_config": null,
|
| 7 |
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"eva_config": null,
|
| 8 |
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"exclude_modules": null,
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| 9 |
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"fan_in_fan_out": false,
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| 10 |
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"inference_mode": true,
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| 11 |
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"init_lora_weights": "pissa",
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| 12 |
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"layer_replication": null,
|
| 13 |
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"layers_pattern": null,
|
| 14 |
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"layers_to_transform": null,
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| 15 |
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"loftq_config": {},
|
| 16 |
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"lora_alpha": 32,
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| 17 |
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"lora_bias": false,
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| 18 |
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"lora_dropout": 0.1,
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| 19 |
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"megatron_config": null,
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| 20 |
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"megatron_core": "megatron.core",
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| 21 |
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"modules_to_save": null,
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| 22 |
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"peft_type": "LORA",
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| 23 |
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"qalora_group_size": 16,
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| 24 |
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"r": 16,
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| 25 |
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"rank_pattern": {},
|
| 26 |
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"revision": null,
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| 27 |
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"target_modules": [
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| 28 |
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"q",
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| 29 |
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"v"
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| 30 |
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],
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| 31 |
+
"target_parameters": null,
|
| 32 |
+
"task_type": "SEQ_2_SEQ_LM",
|
| 33 |
+
"trainable_token_indices": null,
|
| 34 |
+
"use_dora": false,
|
| 35 |
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"use_qalora": false,
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| 36 |
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"use_rslora": true
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| 37 |
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:00f81535a6e6f0b2446ceff1318975787e769ca0c3e194200f89f882f8c23cda
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| 3 |
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size 7098016
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all_results.json
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{
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| 2 |
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"all_params": 224673024,
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| 3 |
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"epoch": 3.0,
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| 4 |
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"memory_footprint": 898692096,
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| 5 |
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"total_flos": 2506179136462848.0,
|
| 6 |
+
"train_loss": 1.8666806372729214,
|
| 7 |
+
"train_runtime": 383.5951,
|
| 8 |
+
"train_samples_per_second": 6.874,
|
| 9 |
+
"train_steps_per_second": 0.86,
|
| 10 |
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"trainable_params": 1769472,
|
| 11 |
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"trainable_params_percent": 0.7875765272113843
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| 12 |
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}
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special_tokens_map.json
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{
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"additional_special_tokens": [
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],
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"eos_token": "</s>",
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| 105 |
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"pad_token": "</s>",
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| 106 |
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"unk_token": "<unk>"
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}
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spiece.model
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
|
| 3 |
+
size 791656
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,939 @@
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| 1 |
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{
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| 2 |
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| 3 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 27 |
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| 29 |
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| 35 |
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| 37 |
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| 38 |
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| 46 |
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| 54 |
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| 61 |
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| 69 |
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| 70 |
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| 75 |
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| 77 |
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| 78 |
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|
| 843 |
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|
| 844 |
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|
| 845 |
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"<extra_id_15>",
|
| 846 |
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|
| 847 |
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"<extra_id_17>",
|
| 848 |
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"<extra_id_18>",
|
| 849 |
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"<extra_id_19>",
|
| 850 |
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"<extra_id_20>",
|
| 851 |
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|
| 852 |
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|
| 853 |
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"<extra_id_23>",
|
| 854 |
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|
| 855 |
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|
| 856 |
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|
| 857 |
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|
| 858 |
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|
| 859 |
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|
| 860 |
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|
| 861 |
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|
| 862 |
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|
| 863 |
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|
| 864 |
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|
| 865 |
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|
| 866 |
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|
| 867 |
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|
| 868 |
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|
| 869 |
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|
| 870 |
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|
| 871 |
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|
| 872 |
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|
| 873 |
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|
| 874 |
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|
| 875 |
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|
| 876 |
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|
| 877 |
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|
| 878 |
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|
| 879 |
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|
| 880 |
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|
| 881 |
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|
| 882 |
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|
| 883 |
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|
| 884 |
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|
| 885 |
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|
| 886 |
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| 887 |
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| 888 |
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| 889 |
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|
| 890 |
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|
| 891 |
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| 892 |
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|
| 893 |
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|
| 894 |
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|
| 895 |
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|
| 896 |
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|
| 897 |
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|
| 898 |
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|
| 899 |
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|
| 900 |
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| 901 |
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|
| 902 |
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|
| 903 |
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|
| 904 |
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|
| 905 |
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| 906 |
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| 907 |
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|
| 908 |
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|
| 909 |
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|
| 910 |
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| 911 |
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| 912 |
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|
| 913 |
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|
| 914 |
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| 915 |
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|
| 916 |
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"<extra_id_86>",
|
| 917 |
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"<extra_id_87>",
|
| 918 |
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"<extra_id_88>",
|
| 919 |
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"<extra_id_89>",
|
| 920 |
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"<extra_id_90>",
|
| 921 |
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"<extra_id_91>",
|
| 922 |
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"<extra_id_92>",
|
| 923 |
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|
| 924 |
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"<extra_id_94>",
|
| 925 |
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|
| 926 |
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|
| 927 |
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|
| 928 |
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"<extra_id_98>",
|
| 929 |
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"<extra_id_99>"
|
| 930 |
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|
| 931 |
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|
| 932 |
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"eos_token": "</s>",
|
| 933 |
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"extra_ids": 100,
|
| 934 |
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|
| 935 |
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"model_max_length": 1000000000000000019884624838656,
|
| 936 |
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"pad_token": "</s>",
|
| 937 |
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"tokenizer_class": "T5Tokenizer",
|
| 938 |
+
"unk_token": "<unk>"
|
| 939 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,12 @@
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|
| 1 |
+
{
|
| 2 |
+
"all_params": 224673024,
|
| 3 |
+
"epoch": 3.0,
|
| 4 |
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"memory_footprint": 898692096,
|
| 5 |
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"total_flos": 2506179136462848.0,
|
| 6 |
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"train_loss": 1.8666806372729214,
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| 7 |
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"train_runtime": 383.5951,
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| 8 |
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"train_samples_per_second": 6.874,
|
| 9 |
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"train_steps_per_second": 0.86,
|
| 10 |
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"trainable_params": 1769472,
|
| 11 |
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"trainable_params_percent": 0.7875765272113843
|
| 12 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,2401 @@
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| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 3.0,
|
| 6 |
+
"eval_steps": 500,
|
| 7 |
+
"global_step": 330,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"epoch": 0.00909090909090909,
|
| 14 |
+
"grad_norm": 5.629480361938477,
|
| 15 |
+
"learning_rate": 0.001,
|
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training_args.bin
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