BeamPraewa
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outs

Automatic Speech Recognition

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outs

This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.8718
Cer: 86.1599

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: 8e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
1.3518	1.0	1073	1.6712	85.1290
0.4101	2.0	2146	1.7400	89.8577
0.1529	3.0	3219	1.8718	86.1599

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

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Safetensors

Model size

0.8B params

Tensor type

F32

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openai/whisper-large-v3

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openai/whisper-large-v3-turbo

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