camembert-finetuned-ner
This model is a fine-tuned version of camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2258
- Precision: 0.8862
- Recall: 0.9023
- F1: 0.8942
- Accuracy: 0.9472
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 |
---|---|---|---|---|---|---|---|
0.2995 | 1.0 | 2500 | 0.2595 | 0.8672 | 0.8846 | 0.8758 | 0.9411 |
0.2017 | 2.0 | 5000 | 0.2181 | 0.8808 | 0.8946 | 0.8877 | 0.9451 |
0.1604 | 3.0 | 7500 | 0.2258 | 0.8862 | 0.9023 | 0.8942 | 0.9472 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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