t5-samsum-demo
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2128
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 8
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.6674 | 1.0 | 461 | 3.4159 |
| 3.507 | 2.0 | 922 | 3.3204 |
| 3.4663 | 3.0 | 1383 | 3.2748 |
| 3.403 | 4.0 | 1844 | 3.2506 |
| 3.3908 | 5.0 | 2305 | 3.2319 |
| 3.367 | 6.0 | 2766 | 3.2222 |
| 3.3747 | 7.0 | 3227 | 3.2145 |
| 3.3739 | 8.0 | 3688 | 3.2128 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Base model
google-t5/t5-small