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---
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
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