whisper-speech-small – AI Model by fatipd | AlphaNeural AI

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whisper-speech-small

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whisper-speech-small

This model is a fine-tuned version of openai/whisper-small on the Google speech dataset. It achieves the following results on the evaluation set:

Loss: 0.0021
Wer: 0.3861

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
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: linear
lr_scheduler_warmup_steps: 250
training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0095	0.2	250	0.0042	0.7239
0.0068	0.4	500	0.0051	1.0135
0.0045	0.6	750	0.0021	0.3861
0.0056	0.8	1000	0.0018	1.5927
0.0021	1.0	1250	0.0023	8.8803
0.0081	1.2	1500	0.0033	2.0270
0.0056	1.4	1750	0.0023	6.1293
0.0028	1.6	2000	0.0017	0.8687
0.0064	1.81	2250	0.0011	0.8687
0.0005	2.01	2500	0.0014	2.0270
0.0015	2.21	2750	0.0013	1.4961
0.0012	2.41	3000	0.0014	1.8822

Framework versions

Transformers 4.30.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3