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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/bart-large-cnn |
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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: Large-dataset-factor |
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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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# Large-dataset-factor |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8394 |
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- Rouge1: 0.6016 |
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- Rouge2: 0.3238 |
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- Rougel: 0.3867 |
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- Rougelsum: 0.3867 |
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- Gen Len: 142.0 |
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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: 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: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 1 | 1.2175 | 0.4598 | 0.2293 | 0.3085 | 0.3085 | 75.5 | |
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| No log | 2.0 | 2 | 1.0135 | 0.5862 | 0.3326 | 0.432 | 0.432 | 114.5 | |
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| No log | 3.0 | 3 | 0.9291 | 0.5584 | 0.2891 | 0.3831 | 0.3831 | 142.0 | |
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| No log | 4.0 | 4 | 0.8851 | 0.5572 | 0.2773 | 0.3739 | 0.3739 | 142.0 | |
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| No log | 5.0 | 5 | 0.8642 | 0.5822 | 0.3125 | 0.3886 | 0.3886 | 142.0 | |
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| No log | 6.0 | 6 | 0.8517 | 0.5725 | 0.2977 | 0.3692 | 0.3692 | 142.0 | |
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| No log | 7.0 | 7 | 0.8427 | 0.6016 | 0.3238 | 0.3867 | 0.3867 | 142.0 | |
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| No log | 8.0 | 8 | 0.8394 | 0.6016 | 0.3238 | 0.3867 | 0.3867 | 142.0 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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