---
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
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# 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: 0.1873
- Precision: 0.9299
- Recall: 0.9409
- F1: 0.9354
- Accuracy: 0.9871

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0417        | 1.0   | 1756  | 0.0945          | 0.9322    | 0.9337 | 0.9330 | 0.9857   |
| 0.0193        | 2.0   | 3512  | 0.1109          | 0.9271    | 0.9368 | 0.9319 | 0.9862   |
| 0.0083        | 3.0   | 5268  | 0.1277          | 0.9273    | 0.9397 | 0.9335 | 0.9869   |
| 0.0035        | 4.0   | 7024  | 0.1552          | 0.9256    | 0.9404 | 0.9329 | 0.9868   |
| 0.0015        | 5.0   | 8780  | 0.1725          | 0.9283    | 0.9397 | 0.9340 | 0.9869   |
| 0.0006        | 6.0   | 10536 | 0.1843          | 0.9304    | 0.9404 | 0.9354 | 0.9870   |
| 0.0005        | 7.0   | 12292 | 0.1863          | 0.9304    | 0.9408 | 0.9355 | 0.9871   |
| 0.0004        | 8.0   | 14048 | 0.1874          | 0.9294    | 0.9406 | 0.9349 | 0.9871   |
| 0.0002        | 9.0   | 15804 | 0.1872          | 0.9299    | 0.9409 | 0.9354 | 0.9871   |
| 0.0002        | 10.0  | 17560 | 0.1873          | 0.9299    | 0.9409 | 0.9354 | 0.9871   |


### Framework versions

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