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whisper-large-english-TG – AI Model by pranjali06 | AlphaNeural AI
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whisper-large-english-TG
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
common_voice_1_0
openai/whisper-large
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-large-english-TG
This model is a fine-tuned version of
openai/whisper-large
on the common_voice dataset. It achieves the following results on the evaluation set:
Loss: 0.4494
Wer: 18.0005
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: 2
total_train_batch_size: 32
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
0.0452
2.6350
1000
0.3455
19.6915
0.0034
5.2701
2000
0.3999
17.8823
0.0005
7.9051
3000
0.4770
18.1438
0.0001
10.5402
4000
0.4494
18.0005
Framework versions
Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.19.1
