bert-tiny-emotion-KD-BERT_and_distilBERT

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.8780
• Accuracy: 0.918

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: 16
• eval_batch_size: 16
• seed: 33
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
7.1848	1.0	1000	4.7404	0.774
3.856	2.0	2000	2.7317	0.8685
2.3973	3.0	3000	1.8329	0.8895
1.5273	4.0	4000	1.2938	0.898
1.113	5.0	5000	1.1298	0.8985
0.9099	6.0	6000	1.0746	0.907
0.831	7.0	7000	1.0071	0.907
0.6813	8.0	8000	0.9556	0.9115
0.6432	9.0	9000	0.9746	0.913
0.5745	10.0	10000	0.8780	0.918
0.5319	11.0	11000	0.9410	0.909
0.4787	12.0	12000	0.9103	0.913
0.4529	13.0	13000	0.8829	0.915

Framework versions

• Transformers 4.22.1
• Pytorch 1.12.1+cu113
• Datasets 2.5.1
• Tokenizers 0.12.1