metadata
library_name: peft
base_model: NousResearch/Llama-2-7b-hf
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: evaluation_model
results: []
evaluation_model
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7124
- Accuracy: 0.4667
- Precision: 0.4577
- Recall: 0.9559
- F1: 0.6190
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.9829 | 43 | 0.9195 | 0.5467 | 0.0 | 0.0 | 0.0 |
| No log | 1.9943 | 87 | 0.6833 | 0.5667 | 0.5172 | 0.6618 | 0.5806 |
| No log | 2.9829 | 130 | 0.6898 | 0.5267 | 0.4884 | 0.9265 | 0.6396 |
| 0.8708 | 3.9943 | 174 | 0.6775 | 0.5667 | 0.5149 | 0.7647 | 0.6154 |
| 0.8708 | 4.9371 | 215 | 0.7124 | 0.4667 | 0.4577 | 0.9559 | 0.6190 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3