whisper-tiny – AI Model by DenBor | AlphaNeural AI

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DenBor/
whisper-tiny

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openai/whisper-tiny

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whisper-tiny

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: 0.6649
Wer Ortho: 0.2984
Wer: 0.2926

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: 16
eval_batch_size: 16
seed: 42
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: 750

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.3212	3.57	100	0.4962	0.3115	0.2974
0.0362	7.14	200	0.5397	0.3096	0.2980
0.0045	10.71	300	0.5860	0.2984	0.2878
0.0015	14.29	400	0.6235	0.3077	0.3027
0.0015	17.86	500	0.6388	0.2984	0.2938
0.0006	21.43	600	0.6467	0.2996	0.2962
0.0006	25.0	700	0.6649	0.2984	0.2926

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.1
Tokenizers 0.13.3