distilbert-base-uncased-finetuned-sst2

This model is a fine-tuned version of distilbert-base-uncased on the sst2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3372
• Accuracy: 0.9025

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: 64
• eval_batch_size: 64
• 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
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1777	1.0	1053	0.2593	0.9014
0.1042	2.0	2106	0.3127	0.8968
0.0575	3.0	3159	0.3372	0.9025

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cpu
• Datasets 3.5.0
• Tokenizers 0.21.0