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--- |
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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: summarise_v7 |
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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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# summarise_v7 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1331 |
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- Rouge2 Precision: 0.3023 |
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- Rouge2 Recall: 0.3298 |
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- Rouge2 Fmeasure: 0.2949 |
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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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- 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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| 1.3257 | 0.22 | 10 | 1.4084 | 0.1157 | 0.4297 | 0.1742 | |
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| 1.6076 | 0.44 | 20 | 1.2212 | 0.337 | 0.3337 | 0.3005 | |
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| 1.1881 | 0.67 | 30 | 1.2107 | 0.3219 | 0.3431 | 0.3095 | |
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| 1.6237 | 0.89 | 40 | 1.1331 | 0.3023 | 0.3298 | 0.2949 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 1.2.1 |
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- Tokenizers 0.12.1 |
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