LawToken-0.5B-baseline
This model is a fine-tuned version of Qwen/Qwen2-0.5B on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.8241
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0668 | 0.13 | 10000 | 1.1084 |
| 0.9744 | 0.27 | 20000 | 1.0197 |
| 0.8864 | 0.4 | 30000 | 0.9631 |
| 0.959 | 0.54 | 40000 | 0.9202 |
| 0.8968 | 0.67 | 50000 | 0.8834 |
| 0.8071 | 0.8 | 60000 | 0.8500 |
| 0.7492 | 0.94 | 70000 | 0.8241 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.19.1
- Tokenizers 0.15.2
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Base model
Qwen/Qwen2-0.5B