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wav2vec2-base-timit-phoneme – AI Model by oosawy | AlphaNeural AI
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oosawy
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wav2vec2-base-timit-phoneme
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
timit_asr
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-base-timit-phoneme
This model is a fine-tuned version of
facebook/wav2vec2-base
on the timit_asr dataset. It achieves the following results on the evaluation set:
Loss: 6.2366
Per: 0.9535
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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 1000
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Per
No log
1.0
13
6.8820
0.9999
No log
2.0
26
6.6526
0.9978
No log
3.0
39
6.2366
0.9535
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu126
Datasets 2.21.0
Tokenizers 0.22.1
