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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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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: bart-base-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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# bart-base-finetuned-cnn_dailymail |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0437 |
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- Rouge1: 25.3365 |
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- Rouge2: 13.3508 |
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- Rougel: 21.4401 |
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- Rougelsum: 23.9107 |
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- Bleu 1: 3.9737 |
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- Bleu 2: 2.7698 |
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- Bleu 3: 2.0856 |
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- Meteor: 12.8165 |
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- Lungime rezumat: 11.6837 |
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- Lungime original: 48.7563 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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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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| 1.3567 | 1.0 | 896 | 1.0741 | 25.256 | 13.2616 | 21.4201 | 23.8469 | 4.0588 | 2.8245 | 2.1231 | 12.7828 | 11.7437 | 48.7563 | |
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| 1.0881 | 2.0 | 1792 | 1.0609 | 25.1093 | 13.0973 | 21.1393 | 23.6685 | 3.943 | 2.7211 | 2.0277 | 12.6304 | 11.758 | 48.7563 | |
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| 1.0172 | 3.0 | 2688 | 1.0445 | 25.2209 | 13.2134 | 21.3199 | 23.8191 | 4.0205 | 2.7985 | 2.0994 | 12.7482 | 11.751 | 48.7563 | |
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| 0.9633 | 4.0 | 3584 | 1.0392 | 25.0763 | 13.145 | 21.1885 | 23.6877 | 3.9164 | 2.7134 | 2.043 | 12.6657 | 11.6963 | 48.7563 | |
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| 0.921 | 5.0 | 4480 | 1.0369 | 25.2214 | 13.3045 | 21.4317 | 23.8493 | 3.9533 | 2.7617 | 2.0827 | 12.7434 | 11.6727 | 48.7563 | |
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| 0.8865 | 6.0 | 5376 | 1.0377 | 25.3824 | 13.4543 | 21.4896 | 24.0024 | 3.9731 | 2.799 | 2.1298 | 12.9173 | 11.6563 | 48.7563 | |
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| 0.8576 | 7.0 | 6272 | 1.0347 | 25.1748 | 13.3232 | 21.3419 | 23.7755 | 3.925 | 2.7544 | 2.089 | 12.7437 | 11.6417 | 48.7563 | |
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| 0.8353 | 8.0 | 7168 | 1.0373 | 25.3485 | 13.3938 | 21.4843 | 23.9589 | 3.9384 | 2.7462 | 2.071 | 12.8098 | 11.6407 | 48.7563 | |
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| 0.8173 | 9.0 | 8064 | 1.0448 | 25.345 | 13.3389 | 21.4394 | 23.9221 | 3.9543 | 2.7587 | 2.0827 | 12.8046 | 11.6827 | 48.7563 | |
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| 0.8044 | 10.0 | 8960 | 1.0437 | 25.3365 | 13.3508 | 21.4401 | 23.9107 | 3.9737 | 2.7698 | 2.0856 | 12.8165 | 11.6837 | 48.7563 | |
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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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