---
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: 0.1664
- Precision: 0.9243
- Recall: 0.9395
- F1: 0.9319
- Accuracy: 0.9860

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.048         | 1.0   | 1756  | 0.0971          | 0.8935    | 0.9082 | 0.9008 | 0.9813   |
| 0.0217        | 2.0   | 3512  | 0.0963          | 0.9182    | 0.9301 | 0.9241 | 0.9852   |
| 0.0113        | 3.0   | 5268  | 0.1081          | 0.9265    | 0.9348 | 0.9306 | 0.9858   |
| 0.0038        | 4.0   | 7024  | 0.1477          | 0.9216    | 0.9379 | 0.9297 | 0.9858   |
| 0.0016        | 5.0   | 8780  | 0.1617          | 0.9199    | 0.9370 | 0.9284 | 0.9855   |
| 0.0007        | 6.0   | 10536 | 0.1618          | 0.9235    | 0.9390 | 0.9312 | 0.9859   |
| 0.0005        | 7.0   | 12292 | 0.1644          | 0.9245    | 0.9395 | 0.9319 | 0.9860   |
| 0.0004        | 8.0   | 14048 | 0.1662          | 0.9248    | 0.9393 | 0.9320 | 0.9861   |
| 0.0003        | 9.0   | 15804 | 0.1664          | 0.9248    | 0.9395 | 0.9321 | 0.9861   |
| 0.0003        | 10.0  | 17560 | 0.1664          | 0.9243    | 0.9395 | 0.9319 | 0.9860   |


### Framework versions

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