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Whisper-fine-tuned-large-v2-company-earnings-call-v0-aws – AI Model by MasatoShima1618 | AlphaNeural AI
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MasatoShima1618
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Whisper-fine-tuned-large-v2-company-earnings-call-v0-aws
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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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Whisper-fine-tuned-large-v2-company-earnings-call-v0-aws
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: 0.0017
Wer: 0.0
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: 8
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
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: 5
training_steps: 40
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
No log
2.5
10
0.0478
6.0594
No log
5.0
20
0.0068
1.5438
0.0895
7.5
30
0.0023
0.0
0.0895
10.0
40
0.0017
0.0
Framework versions
Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2
