| | --- |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - cc_news_es_titles |
| | model-index: |
| | - name: encoder_decoder_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. --> |
| |
|
| | # encoder_decoder_es |
| |
|
| | This model is a fine-tuned version of [](https://huggingface.co/) on the cc_news_es_titles dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 7.8773 |
| | - Rouge2 Precision: 0.002 |
| | - Rouge2 Recall: 0.0116 |
| | - Rouge2 Fmeasure: 0.0034 |
| | |
| | ## 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: 0.003 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 4 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 7.8807 | 1.0 | 5784 | 7.8976 | 0.0023 | 0.012 | 0.0038 | |
| | | 7.8771 | 2.0 | 11568 | 7.8873 | 0.0018 | 0.0099 | 0.003 | |
| | | 7.8588 | 3.0 | 17352 | 7.8819 | 0.0015 | 0.0085 | 0.0025 | |
| | | 7.8507 | 4.0 | 23136 | 7.8773 | 0.002 | 0.0116 | 0.0034 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.12.3 |
| | - Pytorch 1.9.1 |
| | - Datasets 1.15.1 |
| | - Tokenizers 0.10.3 |
| |
|
