EthM300/compare9

results

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

• Loss: 0.4597
• Accuracy: 0.8261

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: 10
• eval_batch_size: 10
• 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	0.6606	0.7391
No log	2.0	18	0.5670	0.7391
No log	3.0	27	0.5086	0.7391
No log	4.0	36	0.5059	0.8261
No log	5.0	45	0.4597	0.8261

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0
• Datasets 3.5.0
• Tokenizers 0.21.1