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--- |
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library_name: transformers |
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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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metrics: |
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- rouge |
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model-index: |
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- name: led_model |
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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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# led_model |
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4363 |
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- Rouge1: 0.7117 |
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- Rouge2: 0.5663 |
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- Rougel: 0.684 |
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- Rougelsum: 0.6843 |
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- Gen Len: 15.7955 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 4 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.6184 | 0.9995 | 546 | 0.4788 | 0.699 | 0.5474 | 0.6691 | 0.6694 | 15.7362 | |
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| 0.4523 | 1.9991 | 1092 | 0.4435 | 0.7029 | 0.5569 | 0.6773 | 0.6773 | 15.6763 | |
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| 0.3732 | 2.9986 | 1638 | 0.4392 | 0.7104 | 0.565 | 0.6826 | 0.6827 | 15.8442 | |
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| 0.3249 | 3.9982 | 2184 | 0.4363 | 0.7117 | 0.5663 | 0.684 | 0.6843 | 15.7955 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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