---
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: 0.2046
- Precision: 0.9273
- Recall: 0.9393
- F1: 0.9333
- Accuracy: 0.9864

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0499        | 1.0   | 1756  | 0.1085          | 0.9196    | 0.9287 | 0.9241 | 0.9845   |
| 0.0233        | 2.0   | 3512  | 0.0997          | 0.9249    | 0.9226 | 0.9237 | 0.9845   |
| 0.0097        | 3.0   | 5268  | 0.1343          | 0.9292    | 0.9386 | 0.9339 | 0.9870   |
| 0.0036        | 4.0   | 7024  | 0.1651          | 0.9245    | 0.9386 | 0.9315 | 0.9864   |
| 0.0012        | 5.0   | 8780  | 0.1839          | 0.9257    | 0.9373 | 0.9315 | 0.9863   |
| 0.0005        | 6.0   | 10536 | 0.2027          | 0.9258    | 0.9386 | 0.9321 | 0.9864   |
| 0.0002        | 7.0   | 12292 | 0.2022          | 0.9276    | 0.9384 | 0.9330 | 0.9864   |
| 0.0002        | 8.0   | 14048 | 0.2040          | 0.9274    | 0.9388 | 0.9331 | 0.9864   |
| 0.0001        | 9.0   | 15804 | 0.2048          | 0.9270    | 0.9393 | 0.9331 | 0.9864   |
| 0.0001        | 10.0  | 17560 | 0.2046          | 0.9273    | 0.9393 | 0.9333 | 0.9864   |


### Framework versions

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