reasoning_test
It achieves the following results on the evaluation set:
- Loss: 0.1194
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0614 | 3.5039 | 25 | 0.0718 |
| 0.0119 | 7.1260 | 50 | 0.0773 |
| 0.0025 | 10.6299 | 75 | 0.0889 |
| 0.0006 | 14.2520 | 100 | 0.1082 |
| 0.0002 | 17.7559 | 125 | 0.1155 |
| 0.0002 | 21.3780 | 150 | 0.1182 |
| 0.0001 | 24.8819 | 175 | 0.1194 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 2