fine_tuned_per_domain_balanced
This model is a fine-tuned version of Qwen/Qwen2-1.5B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1209
- Accuracy: 0.9540
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5664 | 0.0203 | 100 | 0.2706 | 0.8890 |
0.2871 | 0.0406 | 200 | 0.2891 | 0.8871 |
0.2495 | 0.0608 | 300 | 0.2310 | 0.9026 |
0.2414 | 0.0811 | 400 | 0.1710 | 0.9290 |
0.1983 | 0.1014 | 500 | 0.1614 | 0.9332 |
0.198 | 0.1217 | 600 | 0.1482 | 0.9394 |
0.2112 | 0.1419 | 700 | 0.1545 | 0.9443 |
0.1791 | 0.1622 | 800 | 0.1303 | 0.9501 |
0.1707 | 0.1825 | 900 | 0.1822 | 0.9340 |
0.1663 | 0.2028 | 1000 | 0.1297 | 0.9511 |
0.1657 | 0.2230 | 1100 | 0.1433 | 0.9492 |
0.1467 | 0.2433 | 1200 | 0.1107 | 0.9590 |
0.1519 | 0.2636 | 1300 | 0.1250 | 0.9548 |
0.1474 | 0.2839 | 1400 | 0.1045 | 0.9613 |
0.1509 | 0.3041 | 1500 | 0.1180 | 0.9593 |
0.147 | 0.3244 | 1600 | 0.1076 | 0.9588 |
0.1308 | 0.3447 | 1700 | 0.1209 | 0.9540 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
Qwen/Qwen2-1.5B