model_v2
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the news_finetune_train dataset. It achieves the following results on the evaluation set:
- Loss: 0.1931
Model description
SLM for energy multi-label classification task.
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3834 | 0.8 | 100 | 0.3359 |
| 0.337 | 1.6 | 200 | 0.2512 |
| 0.2069 | 2.4 | 300 | 0.2033 |
Framework versions
- PEFT 0.15.2
- Transformers 4.55.0
- Pytorch 2.8.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support