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checkpoints – AI Model by yacoubagbane | AlphaNeural AI
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checkpoints
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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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checkpoints
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: 3.1084
Wer: 1.0
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: 8
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: 500
num_epochs: 30
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
5.4567
0.7962
500
3.1191
1.0
3.0371
1.5924
1000
3.1471
1.0
3.0352
2.3885
1500
3.1423
1.0
3.0396
3.1847
2000
3.1056
1.0
3.0361
3.9809
2500
3.1074
1.0
3.0391
4.7771
3000
3.1084
1.0
Framework versions
Transformers 5.13.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2