---
library_name: peft
tags:
- generated_from_trainer
base_model: NousResearch/Llama-2-7b-hf
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: llama-2-ner
  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. -->

# llama-2-ner

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1250
- Precision: 0.5365
- Recall: 0.5421
- F1: 0.5393
- Accuracy: 0.9778

## 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: 0.0009
- 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
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 39   | 0.1314          | 0.3137    | 0.0842 | 0.1328 | 0.9676   |
| No log        | 2.0   | 78   | 0.1068          | 0.2567    | 0.3526 | 0.2971 | 0.9669   |
| No log        | 3.0   | 117  | 0.0806          | 0.3886    | 0.3579 | 0.3726 | 0.9736   |
| No log        | 4.0   | 156  | 0.0710          | 0.4455    | 0.5158 | 0.4780 | 0.9757   |
| No log        | 5.0   | 195  | 0.0852          | 0.5217    | 0.4421 | 0.4786 | 0.9758   |
| No log        | 6.0   | 234  | 0.1035          | 0.5179    | 0.5316 | 0.5247 | 0.9773   |
| No log        | 7.0   | 273  | 0.1237          | 0.5344    | 0.5316 | 0.5330 | 0.9773   |
| No log        | 8.0   | 312  | 0.1250          | 0.5365    | 0.5421 | 0.5393 | 0.9778   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1