whisper_syl_cv12_pad_lob100__0010 – AI Model by bigmorning | AlphaNeural AI

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bigmorning/
whisper_syl_cv12_pad_lob100__0010

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automatic-speech-recognition

generated_from_keras_callback

openai/whisper-tiny

endpoints_compatible

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whisper_syl_cv12_pad_lob100__0010

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

Train Loss: 2.8713
Train Accuracy: 0.0181
Train Wermet: 0.6484
Validation Loss: 2.5226
Validation Accuracy: 0.0157
Validation Wermet: 0.7017
Epoch: 9

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:

optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Training results

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
5.0233	0.0115	1.6383	3.8616	0.0117	0.9516	0
4.4412	0.0127	0.8560	3.5410	0.0125	0.8971	1
4.0719	0.0138	0.8366	3.2944	0.0132	0.8706	2
3.8091	0.0146	0.8133	3.1691	0.0134	0.8487	3
3.6239	0.0152	0.7866	3.0647	0.0136	0.8282	4
3.4749	0.0156	0.7589	2.9835	0.0139	0.8049	5
3.3444	0.0161	0.7359	2.9351	0.0140	0.7979	6
3.2215	0.0165	0.7138	2.8468	0.0145	0.7589	7
3.0754	0.0172	0.6873	2.7530	0.0148	0.7413	8
2.8713	0.0181	0.6484	2.5226	0.0157	0.7017	9

Framework versions

Transformers 4.33.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3