distilbert-base-uncased-finetuned-ner-finetuned-ner

This model was trained from scratch on the skript dataset. It achieves the following results on the evaluation set:

• Loss: 0.6713
• Precision: 0.0581
• Recall: 0.0450
• F1: 0.0507
• Accuracy: 0.7974

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
No log	1.0	44	0.8207	0.0	0.0	0.0	0.7748
No log	2.0	88	0.7113	0.0405	0.0231	0.0294	0.7889
No log	3.0	132	0.6713	0.0581	0.0450	0.0507	0.7974

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1