distilbert-base-uncased-finetuned-clinc

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

• eval_loss: 3.2777
• eval_accuracy: 0.7387
• eval_runtime: 65.4813
• eval_samples_per_second: 47.342
• eval_steps_per_second: 0.993
• epoch: 1.0
• step: 318

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: 48
• eval_batch_size: 48
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1+cpu
• Datasets 2.12.0
• Tokenizers 0.13.3