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--- |
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library_name: transformers |
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license: bsd-3-clause |
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base_model: pszemraj/led-base-book-summary |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: device |
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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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# device |
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This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.3904 |
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- eval_rouge1: 0.7978 |
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- eval_rouge2: 0.6772 |
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- eval_rougeL: 0.7545 |
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- eval_rougeLsum: 0.7544 |
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- eval_gen_len: 66.6569 |
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- eval_runtime: 455.2333 |
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- eval_samples_per_second: 2.408 |
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- eval_steps_per_second: 0.301 |
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- epoch: 7.0 |
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- step: 3836 |
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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: 2e-05 |
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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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.57.0 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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