---
license: mit
tags:
- generated_from_trainer
model-index:
- name: peft-lora-jul
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# peft-lora-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: 0.0817
- Loc: {'precision': 0.5887445887445888, 'recall': 0.6296296296296297, 'f1': 0.6085011185682326, 'number': 216}
- Misc: {'precision': 0.6111111111111112, 'recall': 0.275, 'f1': 0.3793103448275862, 'number': 40}
- Org: {'precision': 0.7004830917874396, 'recall': 0.725, 'f1': 0.7125307125307125, 'number': 200}
- Per: {'precision': 0.7540106951871658, 'recall': 0.7193877551020408, 'f1': 0.7362924281984334, 'number': 196}
- Overall Precision: 0.6734
- Overall Recall: 0.6641
- Overall F1: 0.6687
- Overall Accuracy: 0.9772

## 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