Expand1_re_30k_tag5_fixed_toolv6
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the Expand1_re_30k_tag5_fixed_toolv6 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2853
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3159 | 0.2103 | 100 | 0.3287 |
| 0.3044 | 0.4206 | 200 | 0.3120 |
| 0.2679 | 0.6309 | 300 | 0.3044 |
| 0.3017 | 0.8412 | 400 | 0.2959 |
| 0.2766 | 1.0515 | 500 | 0.2925 |
| 0.2515 | 1.2618 | 600 | 0.2898 |
| 0.2411 | 1.4721 | 700 | 0.2876 |
| 0.2612 | 1.6824 | 800 | 0.2856 |
| 0.2466 | 1.8927 | 900 | 0.2857 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.8.0+cu128
- Datasets 3.1.0
- Tokenizers 0.20.3
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