Extractor_Adaptor_Qwen3_QA_websrc_second_chance
This model is a fine-tuned version of Qwen/Qwen3-0.6B on the web_finetune_train dataset. It achieves the following results on the evaluation set:
- Loss: 0.0949
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: 8
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.035 | 0.1067 | 50 | 0.1032 |
| 0.0209 | 0.2133 | 100 | 0.1463 |
| 0.0392 | 0.32 | 150 | 0.1112 |
| 0.0424 | 0.4267 | 200 | 0.1135 |
| 0.031 | 0.5333 | 250 | 0.1044 |
| 0.0338 | 0.64 | 300 | 0.0949 |
| 0.0478 | 0.7467 | 350 | 0.1124 |
| 0.0306 | 0.8533 | 400 | 0.1121 |
| 0.0352 | 0.96 | 450 | 0.1222 |
| 0.0193 | 1.0661 | 500 | 0.1458 |
| 0.0332 | 1.1728 | 550 | 0.1522 |
| 0.0264 | 1.2795 | 600 | 0.1254 |
| 0.0246 | 1.3861 | 650 | 0.1313 |
| 0.0201 | 1.4928 | 700 | 0.1422 |
| 0.0151 | 1.5995 | 750 | 0.1459 |
| 0.0206 | 1.7061 | 800 | 0.1486 |
| 0.0166 | 1.8128 | 850 | 0.1476 |
| 0.0189 | 1.9195 | 900 | 0.1466 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.4.1+cu124
- Datasets 4.0.0
- Tokenizers 0.22.1
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