qwen2.5-hh-rm
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8474
- Accuracy: 0.5493
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 8
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5645 | 1.0 | 5310 | 0.7363 | 0.5588 |
| 0.6449 | 2.0 | 10620 | 0.7377 | 0.5521 |
| 0.6083 | 3.0 | 15930 | 0.7829 | 0.5561 |
| 0.6265 | 4.0 | 21240 | 0.7739 | 0.5490 |
| 0.4989 | 5.0 | 26550 | 0.8474 | 0.5493 |
Framework versions
- PEFT 0.12.0
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2
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Qwen/Qwen2.5-1.5B