bert-fine-grained

This model is a fine-tuned version of dbmdz/bert-base-turkish-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1308
• Accuracy: 0.5761
• F1: 0.5655

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: 4e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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	Accuracy	F1
1.0917	1.0	2188	1.0668	0.5789	0.5448
0.9603	2.0	4376	1.0620	0.5868	0.5718
0.8047	3.0	6564	1.1308	0.5761	0.5655

Framework versions

• Transformers 4.21.2
• Pytorch 1.12.1+cu102
• Datasets 2.4.0
• Tokenizers 0.12.1