|
--- |
|
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 |
|
|
