multi-class-bert-base-uncased

This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.8851
• Accuracy: 0.9353
• Recall: 0.8189
• Precision: 0.8263
• F1: 0.8226

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1
No log	1.0	390	1.8851	0.9353	0.8189	0.8263	0.8226

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1
• Datasets 3.2.0
• Tokenizers 0.21.0