hBERTv1_new_pretrain_48_KD_w_init_qnli

gokuls/hBERTv1_new_pretrain_48_KD_w_init_qnli

hBERTv1_new_pretrain_48_KD_w_init_qnli is a text classification model from gokuls. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
Model type: hybridbert
Access: Public
Created: Jun 15, 2023
Updated: Jun 15, 2023
SHA: 42b066ed

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Datasets

glue

Model card

From the Hugging Face model README

hBERTv1_new_pretrain_48_KD_w_init_qnli

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48_KD_wt_init on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.6519
Accuracy: 0.6141

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: 4e-05
train_batch_size: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.671	1.0	819	0.6635	0.5852
0.6464	2.0	1638	0.6519	0.6141
0.6249	3.0	2457	0.6722	0.6035
0.6094	4.0	3276	0.6657	0.6072
0.5982	5.0	4095	0.6642	0.5997
0.5798	6.0	4914	0.6800	0.6125
0.5594	7.0	5733	0.7102	0.6172

Framework versions

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

Task: Text Classification
Library: transformers
Type: hybridbert
Languages: en
Created: Jun 15, 2023
Updated: Jun 15, 2023