tiny-vanilla-target-glue-sst2 – AI Model by muhtasham | AlphaNeural AI

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muhtasham/
tiny-vanilla-target-glue-sst2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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tiny-vanilla-target-glue-sst2

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4800
Accuracy: 0.8245

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6144	0.24	500	0.5259	0.7477
0.4695	0.48	1000	0.4724	0.7752
0.4058	0.71	1500	0.4509	0.7878
0.3815	0.95	2000	0.4536	0.7993
0.3447	1.19	2500	0.4393	0.8073
0.3226	1.43	3000	0.4462	0.8039
0.3065	1.66	3500	0.4392	0.8119
0.2972	1.9	4000	0.4412	0.8096
0.2778	2.14	4500	0.4665	0.8154
0.2599	2.38	5000	0.4395	0.8211
0.2503	2.61	5500	0.4468	0.8245
0.2586	2.85	6000	0.4443	0.8268
0.24	3.09	6500	0.4625	0.8200
0.2353	3.33	7000	0.4556	0.8268
0.2207	3.56	7500	0.4507	0.8291
0.2177	3.8	8000	0.4809	0.8280
0.2156	4.04	8500	0.5157	0.8234
0.2073	4.28	9000	0.4800	0.8245

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.1.dev0
Tokenizers 0.13.2