rudyong
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whisper-tiny-En

Automatic Speech Recognition

Generated from Trainer

Eval Results (legacy)

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whisper-tiny-En

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

Loss: 0.7779
Wer Ortho: 0.3233
Wer: 0.3247

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0001	35.71	500	0.7779	0.3233	0.3247

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

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Base model

openai/whisper-tiny

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(1892)

this model

Dataset used to train rudyong/whisper-tiny-En

Evaluation results

Wer on PolyAI/minds14
self-reported

0.325