t1_25k_v2_tag4
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-7B-Instruct on the t1_25k_v2_tag4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2800
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- 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 |
|---|---|---|---|
| 0.3371 | 0.1698 | 100 | 0.3222 |
| 0.2882 | 0.3396 | 200 | 0.3032 |
| 0.2767 | 0.5093 | 300 | 0.2897 |
| 0.3136 | 0.6791 | 400 | 0.2831 |
| 0.2889 | 0.8489 | 500 | 0.2807 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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