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--- |
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library_name: transformers |
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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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datasets: |
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- arrow |
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model-index: |
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- name: bart-base-2024-09-24_11-12 |
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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-2024-09-24_11-12 |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the arrow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1993 |
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- Gen Len: 20.0 |
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- Bertscorer-p: 0.5928 |
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- Bertscorer-r: 0.1701 |
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- Bertscorer-f1: 0.3731 |
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- Sacrebleu-score: 10.2541 |
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- Sacrebleu-precisions: [90.63003300856309, 79.05155386114873, 70.66565212490137, 65.68935823527592] |
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- Bleu-bp: 0.1350 |
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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: 0.0003 |
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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: 1 |
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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 | Gen Len | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions | Bleu-bp | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:----------------------------------------------------------------------------:|:-------:| |
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| 0.189 | 1.0 | 4772 | 0.1993 | 20.0 | 0.5928 | 0.1701 | 0.3731 | 10.2541 | [90.63003300856309, 79.05155386114873, 70.66565212490137, 65.68935823527592] | 0.1350 | |
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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 3.0.0 |
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- Tokenizers 0.19.1 |
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