NLP-smaller_batch
This model is a fine-tuned version of deepseek-ai/deepseek-coder-7b-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5870
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9188 | 1.0 | 600 | 1.6714 |
| 1.6554 | 2.0 | 1200 | 1.6053 |
| 1.6031 | 3.0 | 1800 | 1.5870 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu118
- 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
Model tree for UNISG-MCS/NLP-smaller_batch
Base model
deepseek-ai/deepseek-coder-6.7b-instruct