peft-prefix-jul
This model is a fine-tuned version of Jean-Baptiste/camembert-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0857
- Loc: {'precision': 0.711864406779661, 'recall': 0.7777777777777778, 'f1': 0.7433628318584071, 'number': 216}
- Misc: {'precision': 0.6956521739130435, 'recall': 0.4, 'f1': 0.507936507936508, 'number': 40}
- Org: {'precision': 0.8097560975609757, 'recall': 0.83, 'f1': 0.8197530864197532, 'number': 200}
- Per: {'precision': 0.8260869565217391, 'recall': 0.7755102040816326, 'f1': 0.8, 'number': 196}
- Overall Precision: 0.7747
- Overall Recall: 0.7699
- Overall F1: 0.7723
- Overall Accuracy: 0.9822
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