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whisper_tuning_2 – AI Model by RecCode | AlphaNeural AI | AlphaNeural AI
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whisper_tuning_2
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper_tuning_2
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 3.8171
Wer: 22.0048
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: 5e-07
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
4.9019
0.2
10
4.7994
22.8435
4.8102
0.4
20
4.3818
22.7236
4.1548
0.6
30
4.0237
22.4042
4.0853
0.8
40
3.8926
22.1246
3.6087
1.0
50
3.8171
22.0048
Framework versions
Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1
