distilbert-base-uncased-finetuned-sst2

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: 0.2584
• Accuracy: 0.9037

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: 2e-05
• train_batch_size: 512
• eval_batch_size: 512
• 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: cosine
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	132	0.2525	0.8956
No log	2.0	264	0.2584	0.9037
No log	3.0	396	0.2673	0.9014

Framework versions

• Transformers 4.57.6
• Pytorch 2.11.0+cu130
• Datasets 4.8.4
• Tokenizers 0.22.2