---
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: 0.1413
- Precision: 0.5320
- Recall: 0.5684
- F1: 0.5496
- Accuracy: 0.9784

## 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   | 0.1312          | 0.1429    | 0.0053 | 0.0102 | 0.9677   |
| No log        | 2.0   | 78   | 0.1077          | 0.3717    | 0.2211 | 0.2772 | 0.9700   |
| No log        | 3.0   | 117  | 0.0770          | 0.4156    | 0.3368 | 0.3721 | 0.9752   |
| No log        | 4.0   | 156  | 0.0683          | 0.4304    | 0.5368 | 0.4778 | 0.9755   |
| No log        | 5.0   | 195  | 0.1069          | 0.4923    | 0.5053 | 0.4987 | 0.9768   |
| No log        | 6.0   | 234  | 0.1214          | 0.5506    | 0.5158 | 0.5326 | 0.9776   |
| No log        | 7.0   | 273  | 0.1393          | 0.5276    | 0.5526 | 0.5398 | 0.9783   |
| No log        | 8.0   | 312  | 0.1413          | 0.5320    | 0.5684 | 0.5496 | 0.9784   |


### Framework versions

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