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--- |
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license: apache-2.0 |
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base_model: allenai/led-base-16384 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- scientific_papers |
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model-index: |
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- name: allenai/led-base-16384 |
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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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# allenai/led-base-16384 |
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the scientific_papers dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7667 |
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- Rouge2 Precision: 0.15 |
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- Rouge2 Recall: 0.0913 |
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- Rouge2 Fmeasure: 0.1075 |
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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: 5e-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: 4 |
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- total_train_batch_size: 8 |
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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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 2.8931 | 0.32 | 10 | 2.9211 | 0.1243 | 0.1206 | 0.1119 | |
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| 3.0026 | 0.64 | 20 | 2.8150 | 0.1589 | 0.1102 | 0.1241 | |
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| 2.7651 | 0.96 | 30 | 2.7667 | 0.15 | 0.0913 | 0.1075 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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