2and3_apps_30k_v4_tag5_sameprompt_processed
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the 2and3_apps_30k_v4_tag5_sameprompt_processed dataset. It achieves the following results on the evaluation set:
- Loss: 0.1502
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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1594 | 0.2740 | 300 | 0.1698 |
| 0.1554 | 0.5479 | 600 | 0.1604 |
| 0.1535 | 0.8219 | 900 | 0.1567 |
| 0.131 | 1.0959 | 1200 | 0.1550 |
| 0.141 | 1.3699 | 1500 | 0.1525 |
| 0.1394 | 1.6438 | 1800 | 0.1511 |
| 0.1439 | 1.9178 | 2100 | 0.1500 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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