| --- |
| license: apache-2.0 |
| base_model: google/long-t5-tglobal-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: long-t5-tglobal-base |
| 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. --> |
|
|
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/theubaada/huggingface/runs/2p17lh0w) |
| # long-t5-tglobal-base |
|
|
| This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9401 |
| - Rouge1: 0.1934 |
| - Rouge2: 0.0269 |
| - Rougel: 0.1151 |
|
|
| ## 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: 4e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - total_eval_batch_size: 4 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 13 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:| |
| | 1.5731 | 0.9996 | 600 | 1.9730 | 0.1342 | 0.0151 | 0.0912 | |
| | 1.3694 | 1.9996 | 1200 | 1.9623 | 0.1371 | 0.0175 | 0.0909 | |
| | 1.9561 | 2.9992 | 1800 | 1.9565 | 0.1423 | 0.0178 | 0.0928 | |
| | 1.0882 | 3.9996 | 2400 | 1.9548 | 0.1417 | 0.0186 | 0.0900 | |
| | 1.4872 | 4.9992 | 3000 | 1.9412 | 0.1581 | 0.0212 | 0.1006 | |
| | 1.4126 | 5.9988 | 3600 | 1.9486 | 0.1589 | 0.0188 | 0.0986 | |
| | 1.1634 | 7.0 | 4201 | 1.9464 | 0.1756 | 0.0229 | 0.1046 | |
| | 0.9541 | 7.9996 | 4801 | 1.9401 | 0.1791 | 0.0243 | 0.1078 | |
| | 0.9153 | 8.9975 | 5400 | 1.9401 | 0.1934 | 0.0269 | 0.1151 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.41.0 |
| - Pytorch 2.2.0 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
