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