wav2vec2-base-timit-demo-google-colab – AI Model by weege007 | AlphaNeural AI

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weege007/
wav2vec2-base-timit-demo-google-colab

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automatic-speech-recognition

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facebook/wav2vec2-base

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wav2vec2-base-timit-demo-google-colab

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: 0.4572
Wer: 0.3320

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: 32
eval_batch_size: 8
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: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2182	4.0	500	0.3727	0.3821
0.1352	8.0	1000	0.4079	0.3818
0.0992	12.0	1500	0.4380	0.3579
0.07	16.0	2000	0.4601	0.3466
0.0514	20.0	2500	0.4377	0.3408
0.0363	24.0	3000	0.4464	0.3368
0.0295	28.0	3500	0.4572	0.3320

Framework versions

Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 1.18.3
Tokenizers 0.21.2