TinyBERT_SST2

Vishnou/TinyBERT_SST2

TinyBERT_SST2 is a text classification model from Vishnou. 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: bert
Access: Public
Created: Nov 15, 2023
Updated: Nov 18, 2023
SHA: 5aa94d56

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Base models

huawei-noah/TinyBERT_General_4L_312D

Datasets

sst2

Model card

From the Hugging Face model README

TinyBERT_SST2

This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on the sst2 dataset. It achieves the following results on the evaluation set:

Loss: 0.5142
Accuracy: 0.8865

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4686	0.06	500	0.4020	0.8337
0.384	0.12	1000	0.3666	0.8360
0.381	0.18	1500	0.3951	0.8337
0.3609	0.24	2000	0.4378	0.8555
0.3616	0.3	2500	0.3743	0.8475
0.3521	0.36	3000	0.3692	0.8589
0.3113	0.42	3500	0.5072	0.8486
0.319	0.48	4000	0.4212	0.8612
0.3034	0.53	4500	0.4555	0.8647
0.3098	0.59	5000	0.4163	0.8635
0.3113	0.65	5500	0.5226	0.8440
0.2949	0.71	6000	0.4137	0.875
0.2977	0.77	6500	0.4775	0.8486
0.3077	0.83	7000	0.4774	0.8693
0.2953	0.89	7500	0.4491	0.8589
0.2846	0.95	8000	0.5228	0.8784
0.292	1.01	8500	0.4801	0.8865
0.2185	1.07	9000	0.4889	0.8933
0.2343	1.13	9500	0.5862	0.8716
0.2667	1.19	10000	0.4796	0.8842
0.252	1.25	10500	0.5181	0.8842
0.2385	1.31	11000	0.5148	0.875
0.2144	1.37	11500	0.5345	0.8704
0.2348	1.43	12000	0.5073	0.8807
0.2166	1.48	12500	0.4885	0.8865
0.2104	1.54	13000	0.6118	0.8658
0.2145	1.6	13500	0.5091	0.8865
0.2098	1.66	14000	0.5221	0.8876
0.2111	1.72	14500	0.5031	0.8888
0.2042	1.78	15000	0.5257	0.8796
0.2091	1.84	15500	0.5175	0.8819
0.2027	1.9	16000	0.5528	0.8784
0.2173	1.96	16500	0.5142	0.8865

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: bert
Created: Nov 15, 2023
Updated: Nov 18, 2023