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End of training

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README.md ADDED
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+ ---
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+ base_model: facebook/bart-base
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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-base-summarization-medical_on_cnn-46
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+ results: []
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+ ---
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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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+
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+ # bart-base-summarization-medical_on_cnn-46
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+
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+ This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 4.0426
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+ - eval_rouge1: 0.1382
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+ - eval_rouge2: 0.0405
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+ - eval_rougeL: 0.1137
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+ - eval_rougeLsum: 0.1254
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+ - eval_gen_len: 20.0
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+ - eval_runtime: 278.1915
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+ - eval_samples_per_second: 3.595
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+ - eval_steps_per_second: 3.595
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+ - step: 0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 46
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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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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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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
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