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--- |
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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: BART1 |
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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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# BART1 |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.8706 |
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- Rouge1: 57.2472 |
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- Rouge2: 23.1787 |
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- Rougel: 41.8726 |
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- Rougelsum: 53.8183 |
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- Gen Len: 234.4232 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 1 |
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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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| 5.8303 | 0.0835 | 100 | 5.6762 | 48.0404 | 16.526 | 33.0315 | 45.2714 | 234.4232 | |
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| 5.2419 | 0.1671 | 200 | 5.1330 | 49.5121 | 17.8978 | 34.5708 | 46.291 | 234.4232 | |
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| 5.0085 | 0.2506 | 300 | 4.8037 | 52.3507 | 19.2179 | 36.3445 | 48.7473 | 234.4232 | |
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| 4.676 | 0.3342 | 400 | 4.5745 | 51.4939 | 19.2534 | 37.2441 | 48.7288 | 234.4232 | |
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| 4.4521 | 0.4177 | 500 | 4.4154 | 52.9389 | 20.2028 | 38.4139 | 49.9981 | 234.4232 | |
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| 4.4572 | 0.5013 | 600 | 4.2389 | 54.6029 | 21.0796 | 39.2355 | 51.1397 | 234.4232 | |
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| 4.2836 | 0.5848 | 700 | 4.1267 | 55.5174 | 22.1184 | 40.2744 | 52.0886 | 234.4232 | |
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| 4.2862 | 0.6684 | 800 | 4.0549 | 56.305 | 22.433 | 40.8636 | 52.6987 | 234.4232 | |
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| 4.0806 | 0.7519 | 900 | 3.9673 | 57.3033 | 22.873 | 41.2543 | 53.5936 | 234.4232 | |
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| 4.0806 | 0.8355 | 1000 | 3.9154 | 56.3519 | 22.7588 | 41.4512 | 52.9385 | 234.4232 | |
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| 3.8885 | 0.9190 | 1100 | 3.8706 | 57.2472 | 23.1787 | 41.8726 | 53.8183 | 234.4232 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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