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wav2vec2-base-timit-demo – AI Model by li1212 | AlphaNeural AI
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li1212
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wav2vec2-base-timit-demo
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-base-timit-demo
This model is a fine-tuned version of
facebook/wav2vec2-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1812
Wer: 0.2367
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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 20
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
2.9596
3.7975
300
2.9788
0.9977
0.6615
7.5949
600
0.4876
0.4255
0.2672
11.3924
900
0.2480
0.2862
0.1877
15.1899
1200
0.1968
0.2488
0.1736
18.9873
1500
0.1808
0.2372
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
