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output_large – AI Model by shtapm | AlphaNeural AI
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shtapm
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output_large
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large
finetune
apache-2.0
endpoints_compatible
us
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output_large
This model is a fine-tuned version of
openai/whisper-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6419
Wer: 25.1240
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
training_steps: 50
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
No log
0.45
10
0.8644
49.3460
No log
0.91
20
0.7146
28.9581
0.8368
1.36
30
0.6654
25.4849
0.8368
1.82
40
0.6558
25.2143
0.3123
2.27
50
0.6419
25.1240
Framework versions
Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
