|
--- |
|
license: mit |
|
base_model: facebook/m2m100_1.2B |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: cs_m2m_0.01_50_v0.2 |
|
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. --> |
|
|
|
# cs_m2m_0.01_50_v0.2 |
|
|
|
This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2B) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 6.9335 |
|
- Bleu: 0.0 |
|
- Gen Len: 5.0 |
|
|
|
## 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: 0.01 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
|
| 16.8785 | 1.0 | 6 | 18.9290 | 0.0 | 200.0 | |
|
| 14.9532 | 2.0 | 12 | 16.0041 | 0.0 | 2.0 | |
|
| 9.473 | 3.0 | 18 | 11.4783 | 0.0 | 200.0 | |
|
| 9.3819 | 4.0 | 24 | 11.3159 | 0.0 | 200.0 | |
|
| 8.2604 | 5.0 | 30 | 10.0462 | 0.0 | 2.0 | |
|
| 7.2006 | 6.0 | 36 | 9.0670 | 0.1706 | 6.0 | |
|
| 7.1892 | 7.0 | 42 | 8.6881 | 0.0 | 200.0 | |
|
| 5.8213 | 8.0 | 48 | 8.4889 | 0.0 | 6.0 | |
|
| 6.088 | 9.0 | 54 | 8.1473 | 0.0 | 2.0 | |
|
| 5.4934 | 10.0 | 60 | 7.8530 | 0.0 | 6.0 | |
|
| 5.3899 | 11.0 | 66 | 7.6030 | 0.0 | 3.0 | |
|
| 5.755 | 12.0 | 72 | 7.2990 | 0.0 | 3.0 | |
|
| 5.902 | 13.0 | 78 | 7.1387 | 0.0 | 6.0 | |
|
| 5.1716 | 14.0 | 84 | 7.3531 | 0.0 | 3.0 | |
|
| 5.384 | 15.0 | 90 | 7.4897 | 0.0 | 3.0 | |
|
| 5.772 | 16.0 | 96 | 7.3353 | 0.0 | 3.0 | |
|
| 6.0137 | 17.0 | 102 | 7.2840 | 0.0 | 6.0 | |
|
| 5.3564 | 18.0 | 108 | 7.2226 | 0.0 | 4.0 | |
|
| 4.6533 | 19.0 | 114 | 6.9603 | 0.0 | 3.0 | |
|
| 5.2785 | 20.0 | 120 | 7.1881 | 0.0 | 4.0 | |
|
| 6.822 | 21.0 | 126 | 7.1262 | 0.0 | 4.0 | |
|
| 5.027 | 22.0 | 132 | 7.5066 | 0.0 | 200.0 | |
|
| 5.2595 | 23.0 | 138 | 7.0461 | 0.0 | 4.0 | |
|
| 5.7311 | 24.0 | 144 | 7.5675 | 0.0 | 200.0 | |
|
| 5.19 | 25.0 | 150 | 6.9761 | 0.0 | 4.0 | |
|
| 5.4136 | 26.0 | 156 | 7.0165 | 0.0 | 6.0 | |
|
| 5.3953 | 27.0 | 162 | 7.0036 | 0.0 | 5.0 | |
|
| 5.1609 | 28.0 | 168 | 7.2334 | 0.0 | 200.0 | |
|
| 4.1589 | 29.0 | 174 | 6.8345 | 0.0 | 3.0 | |
|
| 6.129 | 30.0 | 180 | 7.0334 | 0.0 | 4.0 | |
|
| 3.9707 | 31.0 | 186 | 6.8262 | 0.0 | 4.0 | |
|
| 4.851 | 32.0 | 192 | 6.7521 | 0.0 | 4.0 | |
|
| 4.8473 | 33.0 | 198 | 6.8321 | 0.0 | 4.0 | |
|
| 4.6168 | 34.0 | 204 | 6.8539 | 0.0 | 4.0 | |
|
| 4.304 | 35.0 | 210 | 6.9346 | 0.0 | 4.0 | |
|
| 5.0315 | 36.0 | 216 | 7.0995 | 0.0 | 132.0 | |
|
| 4.5656 | 37.0 | 222 | 6.9738 | 0.0 | 4.0 | |
|
| 4.3283 | 38.0 | 228 | 6.8871 | 0.0 | 4.0 | |
|
| 4.8156 | 39.0 | 234 | 6.9938 | 0.0 | 4.0 | |
|
| 4.6101 | 40.0 | 240 | 7.0034 | 0.0 | 5.0 | |
|
| 5.1564 | 41.0 | 246 | 6.9462 | 0.0 | 5.0 | |
|
| 4.432 | 42.0 | 252 | 7.0158 | 0.0 | 4.0 | |
|
| 5.0996 | 43.0 | 258 | 7.0378 | 0.0 | 5.0 | |
|
| 4.3684 | 44.0 | 264 | 6.9261 | 0.0 | 5.0 | |
|
| 5.2601 | 45.0 | 270 | 6.9520 | 0.0169 | 200.0 | |
|
| 4.4939 | 46.0 | 276 | 6.9559 | 0.0 | 5.0 | |
|
| 4.7493 | 47.0 | 282 | 6.9144 | 0.0 | 5.0 | |
|
| 4.615 | 48.0 | 288 | 6.9272 | 0.0 | 5.0 | |
|
| 5.5171 | 49.0 | 294 | 6.9316 | 0.0 | 5.0 | |
|
| 5.077 | 50.0 | 300 | 6.9335 | 0.0 | 5.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
