End of training

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- cc_news_es_titles
+model-index:
+- name: amazon-sagemaker-community/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. -->
+
+# amazon-sagemaker-community/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