---
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: 0.1511
- Precision: 0.4375
- Recall: 0.4789
- F1: 0.4573
- Accuracy: 0.9752

## 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: 0.0005
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 39   | 0.1580          | 0.0       | 0.0    | 0.0    | 0.9677   |
| No log        | 2.0   | 78   | 0.1313          | 0.2037    | 0.1158 | 0.1477 | 0.9654   |
| No log        | 3.0   | 117  | 0.0948          | 0.3494    | 0.1526 | 0.2125 | 0.9698   |
| No log        | 4.0   | 156  | 0.0952          | 0.2252    | 0.3947 | 0.2868 | 0.9676   |
| No log        | 5.0   | 195  | 0.0850          | 0.3160    | 0.3526 | 0.3333 | 0.9733   |
| No log        | 6.0   | 234  | 0.1012          | 0.2990    | 0.4895 | 0.3713 | 0.9690   |
| No log        | 7.0   | 273  | 0.1282          | 0.4476    | 0.4947 | 0.4700 | 0.9739   |
| No log        | 8.0   | 312  | 0.1400          | 0.4332    | 0.4947 | 0.4619 | 0.9748   |
| No log        | 9.0   | 351  | 0.1492          | 0.4279    | 0.5    | 0.4612 | 0.9753   |
| No log        | 10.0  | 390  | 0.1511          | 0.4375    | 0.4789 | 0.4573 | 0.9752   |


### Framework versions

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