hbertv2-Massive-intent_48_w_in

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 on the massive dataset. It achieves the following results on the evaluation set:

• Loss: 0.8743
• Accuracy: 0.8687

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
1.6541	1.0	180	0.8401	0.7796
0.7252	2.0	360	0.7149	0.8175
0.5019	3.0	540	0.6591	0.8396
0.3604	4.0	720	0.7243	0.8190
0.2653	5.0	900	0.7002	0.8465
0.19	6.0	1080	0.6907	0.8470
0.1458	7.0	1260	0.7161	0.8539
0.1048	8.0	1440	0.7688	0.8534
0.0778	9.0	1620	0.7815	0.8613
0.0551	10.0	1800	0.8321	0.8593
0.0376	11.0	1980	0.8515	0.8647
0.0212	12.0	2160	0.8644	0.8652
0.0154	13.0	2340	0.8743	0.8687
0.0088	14.0	2520	0.8797	0.8657
0.0059	15.0	2700	0.8707	0.8677

Framework versions

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