metadata
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B
tags:
- generated_from_trainer
datasets:
- arrow
model-index:
- name: SLM_LAW
results: []
SLM_LAW
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 1.1380
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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_steps: 1000
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5039 | 0.0248 | 500 | 1.4864 |
| 1.4341 | 0.0496 | 1000 | 1.4603 |
| 1.3489 | 0.0744 | 1500 | 1.3271 |
| 1.2564 | 0.0992 | 2000 | 1.2632 |
| 1.2071 | 0.1240 | 2500 | 1.2287 |
| 1.1771 | 0.1488 | 3000 | 1.2031 |
| 1.1565 | 0.1737 | 3500 | 1.1845 |
| 1.1338 | 0.1985 | 4000 | 1.1688 |
| 1.1158 | 0.2233 | 4500 | 1.1507 |
| 1.0999 | 0.2481 | 5000 | 1.1380 |
Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0