FoRC_S1_BERT

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

• Loss: 1.3170
• Accuracy: 0.6476
• F1: 0.6317

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: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
2.0182	2.0	2596	1.4831	0.6049	0.5673
1.1498	4.0	5192	1.3217	0.6439	0.6224
0.8597	6.0	7788	1.3170	0.6476	0.6317

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.1