Test_sagemaker
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset.
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.9874 | 54 | 0.7080 | 0.5133 | 0.5101 | 0.4731 | 0.4909 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.3.1.post300
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 15
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.
Model tree for viv6267/Test_sagemaker
Base model
NousResearch/Llama-2-7b-hf