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STT_Model_8 – AI Model by LowGI | AlphaNeural AI | AlphaNeural AI
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STT_Model_8
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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STT_Model_8
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5858
Wer: 0.3549
Model description
More information needed
Intended uses & limitations
More information needed
Dataset info
Name: LJSpeech
Source:
https://www.kaggle.com/datasets/mathurinache/the-lj-speech-dataset
Total audios (in Google Drive): 1420
Total transcripts (in Google Drive): 13100
No. of rows selected: 100
Train-test ratio: 80:20
No. of training set: 80
No. of testing set: 20
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0001
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
lr_scheduler_warmup_steps: 1000
num_epochs: 100
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
No log
20.0
200
2.9443
1.0
No log
40.0
400
2.8603
1.0
3.8362
60.0
600
0.5940
0.4197
3.8362
80.0
800
0.5702
0.3380
0.2307
100.0
1000
0.5858
0.3549
Framework versions
Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
