distilbert-finetuned

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: 0.4770
• Accuracy: 0.9014

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.227	1.0	8419	0.4213	0.8819
0.1453	2.0	16838	0.4544	0.8922
0.0816	3.0	25257	0.4770	0.9014

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2