distilbert-base-uncased-finetuned-switchboard-2

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

• Loss: 0.7090
• Accuracy: 0.7215
• Precision: 0.7176
• Recall: 0.7215
• F1: 0.7188

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.2139	1.0	370	0.8510	0.6875	0.6831	0.6875	0.6846
0.3195	2.0	740	0.7090	0.7215	0.7176	0.7215	0.7188

Framework versions

• Transformers 4.13.0
• Pytorch 1.13.0+cu116
• Datasets 1.16.1
• Tokenizers 0.10.3