| --- |
| library_name: peft |
| base_model: owenMills/bart-pas-model |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: bart-pas-lora |
| 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. --> |
|
|
| # bart-pas-lora |
|
|
| This model is a fine-tuned version of [owenMills/bart-pas-model](https://huggingface.co/owenMills/bart-pas-model) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.0678 |
| - Rouge1: 19.51 |
| - Rouge2: 8.76 |
| - Rougel: 17.44 |
| - Rougelsum: 17.41 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| - label_smoothing_factor: 0.1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 4.4614 | 0.96 | 15 | 4.7799 | 15.27 | 6.55 | 12.8 | 13.24 | |
| | 4.3888 | 1.96 | 30 | 4.5425 | 14.55 | 7.1 | 12.76 | 13.17 | |
| | 4.4672 | 2.96 | 45 | 4.3419 | 15.48 | 7.45 | 13.79 | 14.02 | |
| | 3.3327 | 3.96 | 60 | 4.2166 | 15.96 | 8.45 | 14.57 | 14.89 | |
| | 3.5467 | 4.96 | 75 | 4.1432 | 16.18 | 6.44 | 13.94 | 13.99 | |
| | 4.4243 | 5.96 | 90 | 4.1056 | 18.16 | 7.4 | 16.03 | 16.1 | |
| | 4.6372 | 6.96 | 105 | 4.0792 | 18.67 | 8.16 | 16.96 | 16.98 | |
| | 4.4094 | 7.96 | 120 | 4.0678 | 19.51 | 8.76 | 17.44 | 17.41 | |
| | 4.3115 | 8.96 | 135 | 4.0601 | 19.45 | 7.79 | 17.18 | 17.24 | |
| | 4.4145 | 9.96 | 150 | 4.0572 | 19.44 | 7.79 | 17.17 | 17.23 | |
|
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|
|
| ### Framework versions |
|
|
| - PEFT 0.13.2 |
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.4 |
