Token Classification
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Safetensors
French
camembert
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---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembert-base-frenchNER-3_epochs
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. -->
# camembert-base-frenchNER-3_epochs
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0876
- Precision: 0.9292
- Recall: 0.9534
- F1: 0.9411
- Accuracy: 0.9858
## 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: 2e-05
- 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0294 | 1.0 | 43650 | 0.0903 | 0.9202 | 0.9427 | 0.9313 | 0.9835 |
| 0.0202 | 2.0 | 87300 | 0.0852 | 0.9257 | 0.9514 | 0.9383 | 0.9854 |
| 0.0122 | 3.0 | 130950 | 0.0876 | 0.9292 | 0.9534 | 0.9411 | 0.9858 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1
- Datasets 2.14.7
- Tokenizers 0.15.0