---
license: mit
tags:
- generated_from_trainer
model-index:
- name: peft-prefix-jul
  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. -->

# peft-prefix-jul

This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0834
- Loc: {'precision': 0.7203389830508474, 'recall': 0.7870370370370371, 'f1': 0.752212389380531, 'number': 216}
- Misc: {'precision': 0.6923076923076923, 'recall': 0.45, 'f1': 0.5454545454545455, 'number': 40}
- Org: {'precision': 0.8309178743961353, 'recall': 0.86, 'f1': 0.8452088452088452, 'number': 200}
- Per: {'precision': 0.819672131147541, 'recall': 0.7653061224489796, 'f1': 0.7915567282321899, 'number': 196}
- Overall Precision: 0.7822
- Overall Recall: 0.7822
- Overall F1: 0.7822
- Overall Accuracy: 0.9827

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3