_qa_no_context-finetuned-xsum
This model is a fine-tuned version of google/t5-v1_1-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 0.002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 215 | nan |
| No log | 2.0 | 430 | nan |
| 0.0 | 3.0 | 645 | nan |
| 0.0 | 4.0 | 860 | nan |
| 0.0 | 5.0 | 1075 | nan |
| 0.0 | 6.0 | 1290 | nan |
| 0.0 | 7.0 | 1505 | nan |
| 0.0 | 8.0 | 1720 | nan |
| 0.0 | 9.0 | 1935 | nan |
| 0.0 | 10.0 | 2150 | nan |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.1
- Tokenizers 0.21.0