File size: 2,139 Bytes
fe699bc 53935ce fe699bc 53935ce fe699bc 53935ce fe699bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | ---
library_name: peft
license: apache-2.0
base_model: google/mt5-base
tags:
- base_model:adapter:google/mt5-base
- lora
- transformers
model-index:
- name: mT5_tai-lo_to_chinese_LoRA_ver1.0.k
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mT5_tai-lo_to_chinese_LoRA_ver1.0.k
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1796
- Chrf: 16.1759
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 8
- eval_batch_size: 16
- seed: 1
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 4000
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Chrf |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 9.1427 | 0.9337 | 1000 | 3.4432 | 0.1313 |
| 3.6246 | 1.8674 | 2000 | 3.2296 | 0.713 |
| 3.4624 | 2.8011 | 3000 | 3.3720 | 0.2161 |
| 3.2719 | 3.7348 | 4000 | 2.9802 | 2.1503 |
| 3.1149 | 4.6685 | 5000 | 2.8530 | 3.3285 |
| 2.8582 | 5.6022 | 6000 | 2.5916 | 7.6784 |
| 2.6203 | 6.5359 | 7000 | 2.4117 | 7.1325 |
| 2.4322 | 7.4697 | 8000 | 2.3129 | 12.998 |
| 2.2501 | 8.4034 | 9000 | 2.2295 | 11.9602 |
| 2.1502 | 9.3371 | 10000 | 2.1796 | 16.1759 |
### Framework versions
- PEFT 0.19.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2 |