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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bart-large-cnn |
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results: [] |
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pipeline_tag: summarization |
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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-large-cnn |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 2.8506 |
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- eval_rouge1: 0.3613 |
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- eval_rouge2: 0.0744 |
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- eval_rougeL: 0.1665 |
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- eval_rougeLsum: 0.3401 |
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- eval_gen_len: 385.8086 |
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- eval_runtime: 8322.7751 |
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- eval_samples_per_second: 0.151 |
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- eval_steps_per_second: 0.076 |
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- epoch: 0.99 |
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- step: 63 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 128 |
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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: 5 |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
