metadata
base_model: camembert/camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembert-base-finetuned-ner
results: []
camembert-base-finetuned-ner
This model is a fine-tuned version of camembert/camembert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0280
- Precision: 0.9642
- Recall: 0.9675
- F1: 0.9658
- Accuracy: 0.9921
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0316 | 1.0 | 15205 | 0.0300 | 0.9555 | 0.9609 | 0.9582 | 0.9906 |
| 0.0214 | 2.0 | 30410 | 0.0276 | 0.9624 | 0.9668 | 0.9646 | 0.9918 |
| 0.0156 | 3.0 | 45615 | 0.0280 | 0.9642 | 0.9675 | 0.9658 | 0.9921 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3