distilbert-base-uncased_finetuned_Balance_Upsampling_SPEECH_TEXT_DISPLAY_v1 – AI Model by rajesh426 | AlphaNeural AI

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distilbert-base-uncased_finetuned_Balance_Upsampling_SPEECH_TEXT_DISPLAY_v1

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased_finetuned_Balance_Upsampling_SPEECH_TEXT_DISPLAY_v1

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.6982
Accuracy: 0.7759
F1: 0.7743

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5321	1.0	7958	1.3225	0.7271	0.7391
0.2967	2.0	15916	1.3868	0.7574	0.7601
0.1821	3.0	23874	1.4753	0.7513	0.7515
0.1193	4.0	31832	1.7028	0.7588	0.7596
0.0722	5.0	39790	1.8155	0.7615	0.7599
0.041	6.0	47748	2.1622	0.7695	0.7678
0.0258	7.0	55706	2.3871	0.75	0.7462
0.0149	8.0	63664	2.6135	0.7571	0.7524
0.0076	9.0	71622	2.7974	0.7648	0.7617
0.0051	10.0	79580	2.6982	0.7759	0.7743

Framework versions

Transformers 4.22.2
Pytorch 1.10.2
Datasets 2.5.2
Tokenizers 0.12.1