---
base_model: NousResearch/Llama-2-7b-hf
library_name: peft
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: Experiment-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Experiment-2

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6750
- Accuracy: 0.596
- Precision: 0.5869
- Recall: 0.6263
- F1: 0.6060

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.9874 | 54   | 0.6970          | 0.532    | 0.5313    | 0.4785 | 0.5035 |
| No log        | 1.9931 | 109  | 0.6923          | 0.508    | 0.5103    | 0.1989 | 0.2863 |
| 0.694         | 2.9989 | 164  | 0.6888          | 0.5413   | 0.5303    | 0.6586 | 0.5875 |
| 0.694         | 3.9863 | 218  | 0.6926          | 0.5187   | 0.6279    | 0.0726 | 0.1301 |
| 0.694         | 4.992  | 273  | 0.6778          | 0.5947   | 0.6269    | 0.4516 | 0.525  |
| 0.6841        | 5.9977 | 328  | 0.6738          | 0.5827   | 0.5582    | 0.7608 | 0.6439 |
| 0.6841        | 6.9851 | 382  | 0.6701          | 0.5893   | 0.6301    | 0.4167 | 0.5016 |
| 0.6841        | 7.9909 | 437  | 0.6717          | 0.6013   | 0.5835    | 0.6855 | 0.6304 |
| 0.6699        | 8.9966 | 492  | 0.6768          | 0.5787   | 0.5553    | 0.7554 | 0.6401 |
| 0.6699        | 9.8743 | 540  | 0.6750          | 0.596    | 0.5869    | 0.6263 | 0.6060 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.3.1.post300
- Datasets 3.2.0
- Tokenizers 0.20.3