| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - bleu |
| model_index: |
| - name: run1 |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| metric: |
| name: Bleu |
| type: bleu |
| value: 8.4217 |
| --- |
| |
| <!-- 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. --> |
|
|
| # run1 |
|
|
| This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-es](https://huggingface.co/Helsinki-NLP/opus-mt-es-es) on an unkown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.1740 |
| - Bleu: 8.4217 |
| - Gen Len: 15.9457 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
| | No log | 1.0 | 250 | 4.2342 | 0.8889 | 83.4022 | |
| | 4.6818 | 2.0 | 500 | 3.7009 | 4.1671 | 35.587 | |
| | 4.6818 | 3.0 | 750 | 3.4737 | 7.6414 | 23.9674 | |
| | 3.4911 | 4.0 | 1000 | 3.3713 | 7.7512 | 18.6957 | |
| | 3.4911 | 5.0 | 1250 | 3.2689 | 8.0901 | 19.4674 | |
| | 3.0164 | 6.0 | 1500 | 3.2194 | 8.5708 | 25.0543 | |
| | 3.0164 | 7.0 | 1750 | 3.1853 | 9.5275 | 23.9239 | |
| | 2.6954 | 8.0 | 2000 | 3.1562 | 8.5635 | 18.9674 | |
| | 2.6954 | 9.0 | 2250 | 3.1564 | 8.2031 | 17.5978 | |
| | 2.4503 | 10.0 | 2500 | 3.1314 | 8.5638 | 18.1522 | |
| | 2.4503 | 11.0 | 2750 | 3.1511 | 8.8428 | 17.913 | |
| | 2.2554 | 12.0 | 3000 | 3.1513 | 8.1244 | 17.0 | |
| | 2.2554 | 13.0 | 3250 | 3.1664 | 8.0157 | 16.2717 | |
| | 2.1202 | 14.0 | 3500 | 3.1656 | 8.7758 | 16.6087 | |
| | 2.1202 | 15.0 | 3750 | 3.1550 | 8.4637 | 16.4565 | |
| | 2.0082 | 16.0 | 4000 | 3.1702 | 8.2488 | 15.8587 | |
| | 2.0082 | 17.0 | 4250 | 3.1725 | 8.609 | 16.3043 | |
| | 1.9274 | 18.0 | 4500 | 3.1750 | 8.4476 | 15.8043 | |
| | 1.9274 | 19.0 | 4750 | 3.1734 | 8.4753 | 16.5543 | |
| | 1.888 | 20.0 | 5000 | 3.1740 | 8.4217 | 15.9457 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.9.2 |
| - Pytorch 1.9.0+cu102 |
| - Datasets 1.11.1.dev0 |
| - Tokenizers 0.10.3 |
|
|
