whisper_input_decoder_equal_labels_no_force__0005 – AI Model by bigmorning | AlphaNeural AI

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bigmorning/
whisper_input_decoder_equal_labels_no_force__0005

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automatic-speech-recognition

generated_from_keras_callback

openai/whisper-tiny

endpoints_compatible

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whisper_input_decoder_equal_labels_no_force__0005

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: 0.0018
Train Accuracy: 0.0362
Train Wermet: 23.1500
Validation Loss: 0.0013
Validation Accuracy: 0.0266
Validation Wermet: 44.9304
Epoch: 4

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': 1e-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
0.7688	0.0332	32.0424	0.0164	0.0265	57.8712	0
0.0114	0.0362	31.1067	0.0062	0.0266	54.8371	1
0.0048	0.0362	27.0610	0.0030	0.0266	50.1428	2
0.0027	0.0362	24.9672	0.0018	0.0266	48.0741	3
0.0018	0.0362	23.1500	0.0013	0.0266	44.9304	4

Framework versions

Transformers 4.33.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3