distilbert-base-uncased_Up_Sampling_Sub_Category_SPEECH_TEXT_DISPLAY_v1 – AI Model by rajesh426 | AlphaNeural AI

You can deploy this model and start earning money today!

rajesh426/
distilbert-base-uncased_Up_Sampling_Sub_Category_SPEECH_TEXT_DISPLAY_v1

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert-base-uncased_Up_Sampling_Sub_Category_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: 4.9368
Accuracy: 0.6114
F1: 0.6028

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
0.9716	1.0	12171	2.5228	0.5722	0.5740
0.2857	2.0	24342	3.0558	0.5947	0.5923
0.1438	3.0	36513	3.3499	0.6038	0.6007
0.0842	4.0	48684	3.8879	0.5905	0.5875
0.0504	5.0	60855	4.1478	0.5905	0.5906
0.031	6.0	73026	4.5368	0.5924	0.5865
0.0192	7.0	85197	4.6596	0.6042	0.5980
0.01	8.0	97368	4.8874	0.6087	0.6005
0.0051	9.0	109539	5.0120	0.6118	0.6015
0.0022	10.0	121710	4.9368	0.6114	0.6028

Framework versions

Transformers 4.22.2
Pytorch 1.10.2
Datasets 2.5.2
Tokenizers 0.12.1