whisper-tiny-en – AI Model by KoRiF | AlphaNeural AI

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KoRiF/
whisper-tiny-en

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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: 0.8008
Wer Ortho: 0.3523
Wer: 0.3253

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
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
1.593	1.79	50	1.0054	0.5003	0.4185
0.3982	3.57	100	0.7250	0.4121	0.3554
0.2075	5.36	150	0.6898	0.4226	0.3518
0.0957	7.14	200	0.6909	0.4028	0.3371
0.0412	8.93	250	0.7296	0.3695	0.3300
0.0186	10.71	300	0.7522	0.3627	0.3270
0.008	12.5	350	0.7703	0.3584	0.3288
0.0049	14.29	400	0.7756	0.3553	0.3294
0.0032	16.07	450	0.7889	0.3516	0.3235
0.0023	17.86	500	0.8008	0.3523	0.3253

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3