t5-small-openassistant-chat-final-2
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.1257
- Rougel: 0.0828
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: 5e-05
- train_batch_size: 36
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 288
- 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
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougel |
|---|---|---|---|---|
| 3.7576 | 1.0 | 184 | 3.2561 | 0.0764 |
| 3.4768 | 2.0 | 368 | 3.1922 | 0.0811 |
| 3.4223 | 3.0 | 552 | 3.1580 | 0.0835 |
| 3.3925 | 4.0 | 736 | 3.1399 | 0.0825 |
| 3.3752 | 5.0 | 920 | 3.1297 | 0.0830 |
| 3.3685 | 6.0 | 1104 | 3.1257 | 0.0828 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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Model tree for KMH158/t5-small-openassistant-chat-final-2
Base model
google-t5/t5-small