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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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- bleu |
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model-index: |
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- name: cnn-dailymail_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# cnn-dailymail_model |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0614 |
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- Rouge: {'rouge1': 0.244712987386149, 'rouge2': 0.09089741156156833, 'rougeL': 0.20130780704255938, 'rougeLsum': 0.2014458092407283} |
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- Bleu: 0.1054 |
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- Perplexity: 7.8927 |
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- Gen Len: 19.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge | Bleu | Perplexity | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------:|:------:|:----------:|:-------:| |
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| No log | 1.0 | 75 | 2.1554 | {'rouge1': 0.24004289659476444, 'rouge2': 0.08899351952220792, 'rougeL': 0.19620544968984488, 'rougeLsum': 0.19620948547030603} | 0.1014 | None | 19.0 | |
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| No log | 2.0 | 150 | 2.0823 | {'rouge1': 0.2395197299581741, 'rouge2': 0.08874595402755553, 'rougeL': 0.19692733055468523, 'rougeLsum': 0.19727630390573275} | 0.1010 | 8.6314 | 19.0 | |
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| No log | 3.0 | 225 | 2.0659 | {'rouge1': 0.24346041598310222, 'rouge2': 0.09042566103154628, 'rougeL': 0.20046289165406544, 'rougeLsum': 0.2007357619831489} | 0.1041 | 8.0232 | 19.0 | |
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| No log | 4.0 | 300 | 2.0614 | {'rouge1': 0.244712987386149, 'rouge2': 0.09089741156156833, 'rougeL': 0.20130780704255938, 'rougeLsum': 0.2014458092407283} | 0.1054 | 7.8927 | 19.0 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cpu |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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