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asr-tuned – AI Model by misiker | AlphaNeural AI
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asr-tuned
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
minds14
facebook/wav2vec2-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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asr-tuned
This model is a fine-tuned version of
facebook/wav2vec2-base
on the minds14 dataset. It achieves the following results on the evaluation set:
Loss: 14.1277
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 80
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
29.5796
3.4561
100
19.9129
1.0
18.1581
6.9123
200
16.4319
1.0
16.4852
10.3509
300
17.2291
1.0
16.1466
13.8070
400
16.0391
1.0
15.6755
17.2456
500
14.1277
1.0
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
