| --- |
| license: apache-2.0 |
| base_model: google/long-t5-tglobal-xl |
| tags: |
| - generated_from_trainer |
| datasets: |
| - learn3r/summ_screen_fd_bp |
| model-index: |
| - name: longt5_xl_sfd_bp_10 |
| 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. --> |
|
|
| # longt5_xl_sfd_bp_10 |
|
|
| This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/summ_screen_fd_bp dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.8921 |
| |
| ## 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: 0.001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 32 |
| - total_train_batch_size: 256 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant |
| - num_epochs: 20.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.3973 | 0.97 | 14 | 1.9027 | |
| | 1.9188 | 1.95 | 28 | 1.6941 | |
| | 1.4297 | 2.99 | 43 | 1.5011 | |
| | 1.2759 | 3.97 | 57 | 1.5048 | |
| | 1.1421 | 4.94 | 71 | 1.5463 | |
| | 0.9605 | 5.98 | 86 | 1.6270 | |
| | 0.8082 | 6.96 | 100 | 1.7646 | |
| | 0.664 | 8.0 | 115 | 1.7878 | |
| | 0.5471 | 8.97 | 129 | 1.9500 | |
| | 0.4349 | 9.95 | 143 | 1.9657 | |
| | 0.4338 | 10.99 | 158 | 2.1351 | |
| | 0.2887 | 11.97 | 172 | 2.1166 | |
| | 0.2753 | 12.94 | 186 | 2.4357 | |
| | 0.2114 | 13.98 | 201 | 2.5789 | |
| | 0.1805 | 14.96 | 215 | 2.6075 | |
| | 0.1543 | 16.0 | 230 | 2.5597 | |
| | 0.5166 | 16.97 | 244 | 2.5067 | |
| | 0.1117 | 17.95 | 258 | 2.8087 | |
| | 0.0895 | 18.99 | 273 | 2.7578 | |
| | 0.0779 | 19.48 | 280 | 2.8921 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.36.2 |
| - Pytorch 2.1.2+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
|
|
