| --- |
| license: bsd-3-clause |
| base_model: pszemraj/led-base-book-summary |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: device |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # device |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0247 |
| - Rouge1: 0.6269 |
| - Rouge2: 0.3921 |
| - Rougel: 0.5261 |
| - Rougelsum: 0.5266 |
| - Gen Len: 67.5584 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 274 | 1.0933 | 0.5918 | 0.3356 | 0.4785 | 0.4788 | 72.0547 | |
| | 1.1731 | 2.0 | 548 | 1.0177 | 0.5985 | 0.3525 | 0.4902 | 0.4906 | 68.5055 | |
| | 1.1731 | 3.0 | 822 | 0.9976 | 0.6063 | 0.3603 | 0.4982 | 0.4982 | 69.7263 | |
| | 0.7216 | 4.0 | 1096 | 0.9922 | 0.6113 | 0.3735 | 0.5081 | 0.5084 | 68.1861 | |
| | 0.7216 | 5.0 | 1370 | 0.9957 | 0.6193 | 0.3826 | 0.5216 | 0.5217 | 65.4617 | |
| | 0.5252 | 6.0 | 1644 | 1.0127 | 0.6252 | 0.3877 | 0.5231 | 0.5236 | 68.0584 | |
| | 0.5252 | 7.0 | 1918 | 1.0221 | 0.6252 | 0.3897 | 0.5246 | 0.5246 | 67.5931 | |
| | 0.4079 | 8.0 | 2192 | 1.0247 | 0.6269 | 0.3921 | 0.5261 | 0.5266 | 67.5584 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
