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--- |
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base_model: facebook/bart-large |
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library_name: peft |
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license: apache-2.0 |
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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-summarization-medical_on_cnn-43 |
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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-large-summarization-medical_on_cnn-43 |
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co./facebook/bart-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 3.7448 |
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- eval_rouge1: 0.1395 |
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- eval_rouge2: 0.0402 |
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- eval_rougeL: 0.1147 |
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- eval_rougeLsum: 0.1265 |
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- eval_gen_len: 20.0 |
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- eval_runtime: 443.3206 |
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- eval_samples_per_second: 2.256 |
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- eval_steps_per_second: 2.256 |
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- step: 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: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 43 |
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- gradient_accumulation_steps: 4 |
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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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- num_epochs: 6 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
