results

This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1401
• Accuracy: 0.9583
• Precision: 0.9621
• Recall: 0.9583
• F1: 0.9586

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: 9.755035812704661e-05
• train_batch_size: 32
• eval_batch_size: 16
• 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	7	0.2914	0.875	0.9038	0.875	0.8757
No log	2.0	14	0.2127	0.9583	0.9621	0.9583	0.9586
No log	3.0	21	0.1401	0.9583	0.9621	0.9583	0.9586

Framework versions

• Transformers 4.48.0.dev0
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1