whisper-tiny – AI Model by Gwenn-LR | AlphaNeural AI

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Gwenn-LR/
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: 0.5900
Wer Ortho: 0.3103
Wer: 0.3103

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-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
1.7824	1.7857	50	1.0732	0.4565	0.4565
0.3528	3.5714	100	0.4932	0.3745	0.3745
0.1313	5.3571	150	0.5215	0.3430	0.3430
0.035	7.1429	200	0.5468	0.3387	0.3387
0.0103	8.9286	250	0.5900	0.3103	0.3103
0.0085	10.7143	300	0.6345	0.3307	0.3307
0.009	12.5	350	0.6771	0.3418	0.3418
0.0137	14.2857	400	0.6456	0.3374	0.3374
0.0138	16.0714	450	0.6171	0.3294	0.3294
0.0151	17.8571	500	0.7379	0.4312	0.4312

Framework versions

Transformers 4.49.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0