topic_classification

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

• Loss: 2.3890
• Model Preparation Time: 0.0033
• Accuracy: 0.15

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Accuracy
No log	0.3846	5	2.3190	0.0033	0.15
No log	0.7692	10	2.3612	0.0033	0.15
No log	1.1538	15	2.3687	0.0033	0.15
No log	1.5385	20	2.3841	0.0033	0.15
No log	1.9231	25	2.3890	0.0033	0.15
No log	2.3077	30	2.3890	0.0033	0.15

Framework versions

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