bert-base-Massive-intent_48

This model is a fine-tuned version of gokuls/bert_base_48 on the massive dataset. It achieves the following results on the evaluation set:

• Loss: 0.6203
• Accuracy: 0.8623

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: 64
• eval_batch_size: 64
• seed: 33
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6304	1.0	180	0.8747	0.7821
0.6654	2.0	360	0.6418	0.8347
0.4063	3.0	540	0.5890	0.8529
0.2592	4.0	720	0.6132	0.8446
0.1832	5.0	900	0.6417	0.8519
0.1357	6.0	1080	0.6203	0.8623
0.0969	7.0	1260	0.6742	0.8534
0.0735	8.0	1440	0.7212	0.8436
0.0532	9.0	1620	0.7192	0.8529
0.0378	10.0	1800	0.7625	0.8564
0.0298	11.0	1980	0.7275	0.8588

Framework versions

• Transformers 4.30.2
• Pytorch 1.14.0a0+410ce96
• Datasets 2.13.0
• Tokenizers 0.13.3