---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: billm-mistral-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-mistral-7b-conll03-ner

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1704
- Precision: 0.9275
- Recall: 0.9391
- F1: 0.9333
- Accuracy: 0.9868

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0449        | 1.0   | 1756  | 0.1034          | 0.9239    | 0.9330 | 0.9284 | 0.9857   |
| 0.0225        | 2.0   | 3512  | 0.1098          | 0.9210    | 0.9301 | 0.9256 | 0.9853   |
| 0.0121        | 3.0   | 5268  | 0.1104          | 0.9276    | 0.9346 | 0.9311 | 0.9864   |
| 0.0057        | 4.0   | 7024  | 0.1408          | 0.9232    | 0.9370 | 0.9300 | 0.9863   |
| 0.0023        | 5.0   | 8780  | 0.1538          | 0.9245    | 0.9373 | 0.9309 | 0.9865   |
| 0.0011        | 6.0   | 10536 | 0.1660          | 0.9275    | 0.9393 | 0.9334 | 0.9868   |
| 0.0008        | 7.0   | 12292 | 0.1708          | 0.9283    | 0.9393 | 0.9338 | 0.9869   |
| 0.0006        | 8.0   | 14048 | 0.1710          | 0.9280    | 0.9395 | 0.9337 | 0.9869   |
| 0.0004        | 9.0   | 15804 | 0.1706          | 0.9276    | 0.9391 | 0.9333 | 0.9869   |
| 0.0003        | 10.0  | 17560 | 0.1704          | 0.9275    | 0.9391 | 0.9333 | 0.9868   |


### Framework versions

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