| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: Text_Summarization |
| 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. --> |
|
|
| # my_text_sum_model |
| |
| This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.1211 |
| - Rouge1: 0.3212 |
| - Rouge2: 0.1225 |
| - Rougel: 0.2329 |
| - Rougelsum: 0.2327 |
| - Gen Len: 65.4998 |
| |
| ## 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: 4 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 1.8113 | 1.0 | 1134 | 1.7859 | 0.3221 | 0.1245 | 0.2348 | 0.2348 | 64.0653 | |
| | 1.3327 | 2.0 | 2268 | 1.8142 | 0.3248 | 0.1255 | 0.2368 | 0.2368 | 64.2325 | |
| | 0.9968 | 3.0 | 3402 | 1.9795 | 0.3215 | 0.1236 | 0.2335 | 0.2335 | 65.0935 | |
| | 0.7786 | 4.0 | 4536 | 2.1211 | 0.3212 | 0.1225 | 0.2329 | 0.2327 | 65.4998 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.29.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
| |
