wav2vec2-base-scl-common-voice – AI Model by mazhar00968 | AlphaNeural AI

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mazhar00968/
wav2vec2-base-scl-common-voice

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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wav2vec2-base-scl-common-voice

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: 1.7258
Wer: 0.8720

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: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
7.6627	4.8077	500	3.1642	1.0
1.9566	9.6154	1000	1.3902	0.9209
0.6485	14.4231	1500	1.4672	0.8966
0.4033	19.2308	2000	1.5901	0.9092
0.2760	24.0385	2500	1.6703	0.8878
0.2079	28.8462	3000	1.7262	0.8703
0.2079	30.0	3120	1.7258	0.8720

Framework versions

Transformers 5.12.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2