| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: inetuned-summarize-test |
| | 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. --> |
| |
|
| | # inetuned-summarize-test |
| |
|
| | This model is a fine-tuned version of [minnehwg/inetuned-summarize-test](https://huggingface.co/minnehwg/inetuned-summarize-test) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8961 |
| | - Rouge1: 34.2527 |
| | - Rouge2: 14.2278 |
| | - Rougel: 24.7229 |
| | - Rougelsum: 25.3930 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.05 |
| | - num_epochs: 3 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | | No log | 1.0 | 250 | 0.9249 | 34.2996 | 13.7194 | 24.5150 | 25.1146 | |
| | | 0.6471 | 2.0 | 500 | 0.9104 | 34.1716 | 14.0356 | 24.6683 | 25.1958 | |
| | | 0.6471 | 3.0 | 750 | 0.8961 | 34.2527 | 14.2278 | 24.7229 | 25.3930 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
