promptly-tuned
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3650
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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use 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 |
|---|---|---|---|
| 11.2538 | 1.0 | 7 | 1.4416 |
| 24.3241 | 2.0 | 14 | 1.3788 |
| 11.9827 | 3.0 | 21 | 1.3650 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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