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finetuning_dog – AI Model by unanam | AlphaNeural AI
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unanam
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finetuning_dog
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large-v2
finetune
apache-2.0
endpoints_compatible
us
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finetuning_dog
This model is a fine-tuned version of
openai/whisper-large-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2932
Cer: 8.8686
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-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
Cer
0.0863
2.76
1000
0.2303
9.1216
0.0154
5.52
2000
0.2505
8.6437
0.002
8.29
3000
0.2877
8.6297
0.0021
11.05
4000
0.2932
8.8686
Framework versions
Transformers 4.38.2
Pytorch 2.0.0
Datasets 2.18.0
Tokenizers 0.15.2
