qwen25_math_acc_rm
This model is a fine-tuned version of Jennny/qwen25_7b_sft_math on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2156
- Accuracy: 0.65
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW 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: 0.03
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3308 | 0.2424 | 10 | 1.3608 | 0.66 |
| 0.0063 | 0.4848 | 20 | 1.4237 | 0.7167 |
| 0.0703 | 0.7273 | 30 | 2.4097 | 0.6267 |
| 0.0751 | 0.9697 | 40 | 0.9876 | 0.67 |
| 0.0047 | 1.1939 | 50 | 1.9047 | 0.68 |
| 0.0009 | 1.4364 | 60 | 2.5391 | 0.6267 |
| 0.1065 | 1.6788 | 70 | 2.4082 | 0.64 |
| 0.1204 | 1.9212 | 80 | 2.2156 | 0.65 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1
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