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whisper-small-tg – AI Model by muhtasham | AlphaNeural AI
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muhtasham
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whisper-small-tg
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
whisper-event
hf-asr-leaderboard
tg
apache-2.0
model-index
endpoints_compatible
us
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whisper-small-tg
This model is a fine-tuned version of
openai/whisper-small
on the
google/fleurs
dataset. It achieves the following results on the evaluation set:
Loss: 0.6917
Wer: 28.3622
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: 64
eval_batch_size: 32
seed: 42
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
0.0011
25.0
1000
0.5801
28.1310
0.0004
50.0
2000
0.6423
28.2620
0.0002
75.0
3000
0.6796
28.3931
0.0002
100.0
4000
0.6917
28.3622
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2
