2and3_apps_3k_v4
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the 2and3_apps_3k_v4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2055
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: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- 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
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2332 | 0.1381 | 100 | 0.2561 |
| 0.266 | 0.2762 | 200 | 0.2426 |
| 0.2568 | 0.4144 | 300 | 0.2376 |
| 0.2162 | 0.5525 | 400 | 0.2205 |
| 0.1853 | 0.6906 | 500 | 0.2124 |
| 0.2028 | 0.8287 | 600 | 0.2076 |
| 0.1783 | 0.9669 | 700 | 0.2061 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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