interview_classifier

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

• Loss: 2.0881
• Accuracy: 0.2593

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: 1e-05
• train_batch_size: 2
• eval_batch_size: 2
• 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	54	2.2885	0.1481
No log	2.0	108	2.2611	0.1481
No log	3.0	162	2.2186	0.2593
No log	4.0	216	2.1877	0.2222
No log	5.0	270	2.1593	0.2593
No log	6.0	324	2.1332	0.2593
No log	7.0	378	2.1185	0.2963
No log	8.0	432	2.0965	0.2593
No log	9.0	486	2.0914	0.2593
1.9418	10.0	540	2.0881	0.2593

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0