ternary_support_eval_base_227_voices_transcriptions – AI Model by rezaFarsh | AlphaNeural AI

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rezaFarsh/
ternary_support_eval_base_227_voices_transcriptions

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-uncased

autotrain_compatible

endpoints_compatible

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ternary_support_eval_base_227_voices_transcriptions

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

Loss: 0.5979
Accuracy: 0.9130
F1 Score: 0.8919

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: 1
eval_batch_size: 1
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 Score
1.2416	1.0	204	1.3783	0.6957	0.5708
1.2416	2.0	408	1.4377	0.6957	0.5708
1.4314	3.0	612	1.4118	0.6957	0.5708
1.4314	4.0	816	1.2822	0.6957	0.5708
1.3906	5.0	1020	1.3876	0.6957	0.5708
1.3906	6.0	1224	0.9901	0.7391	0.7152
1.3906	7.0	1428	0.7957	0.8261	0.8116
1.0941	8.0	1632	0.8328	0.8696	0.8498
1.0941	9.0	1836	0.5979	0.9130	0.8919
0.5454	10.0	2040	0.6083	0.9130	0.8919

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1