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whisper-small-hi – AI Model by M2LabOrg | AlphaNeural AI
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whisper-small-hi
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
hi
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper small hi - Michel Mesquita
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.5847
Wer: 34.2081
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0083
9.7800
1000
0.4199
34.7456
0.0003
19.5599
2000
0.5292
34.3351
0.0001
29.3399
3000
0.5721
34.2462
0.0001
39.1198
4000
0.5847
34.2081
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
