---
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: NousResearch/Llama-2-7b-hf
model-index:
- name: billm-llama-7b-conll03-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. -->

# billm-llama-7b-conll03-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: 0.1783
- Precision: 0.9150
- Recall: 0.9330
- F1: 0.9239
- Accuracy: 0.9851

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0477        | 1.0   | 1756  | 0.0998          | 0.9116    | 0.9283 | 0.9199 | 0.9842   |
| 0.0201        | 2.0   | 3512  | 0.0986          | 0.9152    | 0.9251 | 0.9201 | 0.9842   |
| 0.0089        | 3.0   | 5268  | 0.1195          | 0.9128    | 0.9278 | 0.9202 | 0.9843   |
| 0.0025        | 4.0   | 7024  | 0.1564          | 0.9129    | 0.9341 | 0.9234 | 0.9851   |
| 0.0013        | 5.0   | 8780  | 0.1669          | 0.9140    | 0.9316 | 0.9227 | 0.9850   |
| 0.0006        | 6.0   | 10536 | 0.1736          | 0.9155    | 0.9328 | 0.9241 | 0.9852   |
| 0.0003        | 7.0   | 12292 | 0.1755          | 0.9144    | 0.9325 | 0.9233 | 0.9851   |
| 0.0003        | 8.0   | 14048 | 0.1782          | 0.9145    | 0.9328 | 0.9236 | 0.9851   |
| 0.0003        | 9.0   | 15804 | 0.1782          | 0.9144    | 0.9326 | 0.9234 | 0.9851   |
| 0.0002        | 10.0  | 17560 | 0.1783          | 0.9150    | 0.9330 | 0.9239 | 0.9851   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.16.0
- Tokenizers 0.15.0