bert-base-uncased-finetuned-clinc_oos

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

• Loss: 1.0863
• Accuracy: {'accuracy': 0.8672727272727273}
• F1: {'f1': 0.8593551627139002}

Model Training Details

Parameter	Value
Task	text-classification
Base Model Name	bert-base-uncased
Dataset Name	clinc_oos
Dataset Config	plus
Batch Size	16
Number of Epochs	3
Learning Rate	0.00002

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
4.3415	1.0	954	2.4724	{'accuracy': 0.7769090909090909}	{'f1': 0.7596942777117995}
1.7949	2.0	1908	1.3415	{'accuracy': 0.8538181818181818}	{'f1': 0.8441232118060242}
0.8898	3.0	2862	1.0863	{'accuracy': 0.8672727272727273}	{'f1': 0.8593551627139002}

Framework versions

• Transformers 4.33.3
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3