| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: mt5-small-finetuned-amazon-en-es |
| 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-small-finetuned-amazon-en-es |
|
|
| This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.0318 |
| - Rouge1: 0.1806 |
| - Rouge2: 0.0917 |
| - Rougel: 0.1765 |
| - Rougelsum: 0.1766 |
|
|
| ## 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: 5.6e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 6.6121 | 1.0 | 1209 | 3.2969 | 0.1522 | 0.0635 | 0.1476 | 0.147 | |
| | 3.901 | 2.0 | 2418 | 3.1307 | 0.1672 | 0.0821 | 0.1604 | 0.1602 | |
| | 3.5788 | 3.0 | 3627 | 3.0910 | 0.1804 | 0.0922 | 0.1748 | 0.1751 | |
| | 3.4198 | 4.0 | 4836 | 3.0646 | 0.1717 | 0.0813 | 0.167 | 0.1664 | |
| | 3.321 | 5.0 | 6045 | 3.0659 | 0.1782 | 0.0877 | 0.1759 | 0.1756 | |
| | 3.2441 | 6.0 | 7254 | 3.0407 | 0.1785 | 0.088 | 0.1755 | 0.1751 | |
| | 3.2075 | 7.0 | 8463 | 3.0356 | 0.1789 | 0.09 | 0.1743 | 0.1747 | |
| | 3.1803 | 8.0 | 9672 | 3.0318 | 0.1806 | 0.0917 | 0.1765 | 0.1766 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.2 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
