model

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: 0.8202
• Accuracy: 0.6334
• Macro F1: 0.6289

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 OptimizerNames.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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
0.8412	1.0	748	0.8300	0.6027	0.6070
0.6247	2.0	1496	0.8202	0.6334	0.6289

Framework versions

• Transformers 4.57.6
• Pytorch 2.11.0+cpu
• Datasets 2.21.0
• Tokenizers 0.22.2