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--- |
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base_model: google/pegasus-large |
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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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model-index: |
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- name: pegasus-large-finetuned-cnn_dailymail |
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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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# pegasus-large-finetuned-cnn_dailymail |
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This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0469 |
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- Rouge1: 45.2373 |
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- Rouge2: 22.4813 |
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- Rougel: 31.8329 |
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- Rougelsum: 41.6862 |
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- Bleu 1: 34.8304 |
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- Bleu 2: 23.4162 |
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- Bleu 3: 17.4357 |
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- Meteor: 35.0815 |
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- Lungime rezumat: 56.5898 |
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- Lungime original: 48.7656 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:| |
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| 1.2058 | 1.0 | 7165 | 1.0640 | 44.5245 | 22.1439 | 31.4275 | 40.9808 | 33.9802 | 22.8183 | 16.9712 | 34.1035 | 55.245 | 48.7656 | |
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| 1.0602 | 2.0 | 14330 | 1.0534 | 44.7088 | 22.1286 | 31.3398 | 41.0804 | 34.1571 | 22.9231 | 17.0479 | 35.1782 | 59.6166 | 48.7656 | |
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| 1.0144 | 3.0 | 21495 | 1.0479 | 45.0257 | 22.3325 | 31.7313 | 41.4189 | 34.6084 | 23.227 | 17.2859 | 34.7757 | 56.1443 | 48.7656 | |
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| 0.9875 | 4.0 | 28660 | 1.0469 | 45.2373 | 22.4813 | 31.8329 | 41.6862 | 34.8304 | 23.4162 | 17.4357 | 35.0815 | 56.5898 | 48.7656 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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