---
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: llama2-7B-ReqORNot
  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. -->

# llama2-7B-ReqORNot

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2597
- Accuracy: 0.8970
- Weighted precision: 0.8971
- Weighted recall: 0.8970
- Weighted f1: 0.8971
- Macro precision: 0.8969
- Macro recall: 0.8971
- Macro f1: 0.8970

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted precision | Weighted recall | Weighted f1 | Macro precision | Macro recall | Macro f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------:|:--------:|
| No log        | 1.0   | 237  | 0.4807          | 0.7896   | 0.7895             | 0.7896          | 0.7895      | 0.7894          | 0.7891       | 0.7892   |
| No log        | 2.0   | 474  | 0.3167          | 0.8605   | 0.8605             | 0.8605          | 0.8605      | 0.8604          | 0.8604       | 0.8604   |
| 0.5108        | 3.0   | 711  | 0.2709          | 0.8860   | 0.8869             | 0.8860          | 0.8860      | 0.8862          | 0.8866       | 0.8860   |
| 0.5108        | 4.0   | 948  | 0.2704          | 0.8880   | 0.8889             | 0.8880          | 0.8879      | 0.8894          | 0.8871       | 0.8876   |
| 0.1829        | 5.0   | 1185 | 0.2597          | 0.8970   | 0.8971             | 0.8970          | 0.8971      | 0.8969          | 0.8971       | 0.8970   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2