bert-fine-tuned-cola

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

• Loss: 0.8013
• Matthews Correlation: 0.5941

Using pipeline

sentence = "Hi,Not me" #sentence you want to classify

classifier = pipeline("text-classification", model= "syedmubarish/bert-fine-tuned-cola")
classifier(sentence)

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 adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.4624	1.0	1069	0.4426	0.5394
0.3086	2.0	2138	0.5806	0.5828
0.1825	3.0	3207	0.8013	0.5941

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0
• Datasets 4.1.1
• Tokenizers 0.22.1