PEFT
Safetensors
gemma2
axolotl
Generated from Trainer
Paladiso commited on
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End of training

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  1. README.md +15 -18
README.md CHANGED
@@ -1,14 +1,14 @@
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  ---
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  library_name: peft
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- license: apache-2.0
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- base_model: TinyLlama/TinyLlama_v1.1
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  tags:
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  - axolotl
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  - generated_from_trainer
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  datasets:
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- - Paladiso/dataset_4a99212a-ed04-4c6f-b7e3-a8796dfe5605
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  model-index:
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- - name: b77db938-be5a-42dc-a716-d6f0670735e9
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  results: []
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  ---
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@@ -21,16 +21,15 @@ should probably proofread and complete it, then remove this comment. -->
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  axolotl version: `0.6.0`
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  ```yaml
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  adapter: lora
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- base_model: TinyLlama/TinyLlama_v1.1
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  bf16: auto
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  chat_template: llama3
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  dataset_prepared_path: /workspace/axolotl/data/prepared
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  datasets:
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  - ds_type: json
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  format: custom
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- path: Paladiso/dataset_4a99212a-ed04-4c6f-b7e3-a8796dfe5605
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  type:
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- field_input: ''
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  field_instruction: instruction
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  field_output: output
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  system_format: '{system}'
@@ -48,7 +47,7 @@ fsdp_config: null
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  gradient_accumulation_steps: 4
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  gradient_checkpointing: false
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  group_by_length: false
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- hub_model_id: Paladiso/b77db938-be5a-42dc-a716-d6f0670735e9
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  hub_private_repo: true
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  hub_repo: null
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  hub_strategy: checkpoint
@@ -79,8 +78,6 @@ sample_packing: false
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  save_safetensors: true
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  saves_per_epoch: 4
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  sequence_len: 512
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- special_tokens:
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- pad_token: </s>
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  strict: false
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  tf32: false
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  tokenizer_type: AutoTokenizer
@@ -90,10 +87,10 @@ use_accelerate: true
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  val_set_size: 0.05
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  wandb_entity: null
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  wandb_mode: online
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- wandb_name: 4a99212a-ed04-4c6f-b7e3-a8796dfe5605
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  wandb_project: Gradients-On-Demand
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  wandb_run: your_name
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- wandb_runid: 4a99212a-ed04-4c6f-b7e3-a8796dfe5605
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  warmup_steps: 10
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  weight_decay: 0.0
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  xformers_attention: null
@@ -102,11 +99,11 @@ xformers_attention: null
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  </details><br>
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- # b77db938-be5a-42dc-a716-d6f0670735e9
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- This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co/TinyLlama/TinyLlama_v1.1) on the Paladiso/dataset_4a99212a-ed04-4c6f-b7e3-a8796dfe5605 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.1746
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  ## Model description
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@@ -140,9 +137,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- | 2.688 | 0.0005 | 3 | 3.3686 |
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- | 2.7628 | 0.0010 | 6 | 3.2964 |
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- | 4.2762 | 0.0015 | 9 | 3.1746 |
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  ### Framework versions
 
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  ---
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  library_name: peft
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+ license: gemma
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+ base_model: unsloth/gemma-2-2b-it
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  tags:
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  - axolotl
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  - generated_from_trainer
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  datasets:
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+ - Paladiso/dataset_e0ed89fb-80e3-4383-8dd1-e5d47cb56894
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  model-index:
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+ - name: a31e9467-1b84-42f8-a0e6-2c16bbde2ff7
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  results: []
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  ---
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  axolotl version: `0.6.0`
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  ```yaml
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  adapter: lora
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+ base_model: unsloth/gemma-2-2b-it
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  bf16: auto
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  chat_template: llama3
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  dataset_prepared_path: /workspace/axolotl/data/prepared
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  datasets:
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  - ds_type: json
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  format: custom
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+ path: Paladiso/dataset_e0ed89fb-80e3-4383-8dd1-e5d47cb56894
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  type:
 
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  field_instruction: instruction
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  field_output: output
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  system_format: '{system}'
 
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  gradient_accumulation_steps: 4
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  gradient_checkpointing: false
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  group_by_length: false
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+ hub_model_id: Paladiso/a31e9467-1b84-42f8-a0e6-2c16bbde2ff7
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  hub_private_repo: true
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  hub_repo: null
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  hub_strategy: checkpoint
 
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  save_safetensors: true
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  saves_per_epoch: 4
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  sequence_len: 512
 
 
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  strict: false
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  tf32: false
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  tokenizer_type: AutoTokenizer
 
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  val_set_size: 0.05
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  wandb_entity: null
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  wandb_mode: online
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+ wandb_name: e0ed89fb-80e3-4383-8dd1-e5d47cb56894
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  wandb_project: Gradients-On-Demand
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  wandb_run: your_name
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+ wandb_runid: e0ed89fb-80e3-4383-8dd1-e5d47cb56894
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  warmup_steps: 10
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  weight_decay: 0.0
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  xformers_attention: null
 
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  </details><br>
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+ # a31e9467-1b84-42f8-a0e6-2c16bbde2ff7
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+ This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the Paladiso/dataset_e0ed89fb-80e3-4383-8dd1-e5d47cb56894 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3201
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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+ | 1.3971 | 0.0009 | 3 | 1.5252 |
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+ | 1.4187 | 0.0018 | 6 | 1.4485 |
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+ | 1.34 | 0.0026 | 9 | 1.3201 |
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  ### Framework versions