metadata
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Llama-2-7b-hf-IDMGSP
results: []
Llama-2-7b-hf-IDMGSP
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1450
- Accuracy: {'accuracy': 0.9759036144578314}
- F1: {'f1': 0.9758125472411187}
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0766 | 1.0 | 498 | 0.1165 | {'accuracy': 0.9614708835341366} | {'f1': 0.9612813721780804} |
| 0.182 | 2.0 | 996 | 0.0934 | {'accuracy': 0.9657379518072289} | {'f1': 0.9648059816939539} |
| 0.037 | 3.0 | 1494 | 0.1190 | {'accuracy': 0.9716365461847389} | {'f1': 0.9710182097973841} |
| 0.0349 | 4.0 | 1992 | 0.1884 | {'accuracy': 0.96875} | {'f1': 0.9692326702088224} |
| 0.0046 | 5.0 | 2490 | 0.1450 | {'accuracy': 0.9759036144578314} | {'f1': 0.9758125472411187} |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1