whisper_input_decoder_shift_r_labels_with_force__0005 – AI Model by bigmorning | AlphaNeural AI

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bigmorning/
whisper_input_decoder_shift_r_labels_with_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_shift_r_labels_with_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: 4.2445
Train Accuracy: 0.0119
Train Wermet: 0.8228
Validation Loss: 3.6283
Validation Accuracy: 0.0108
Validation Wermet: 0.8695
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
5.6249	0.0091	1.7162	4.2965	0.0094	0.9447	0
4.9223	0.0099	0.9041	4.1562	0.0097	0.9327	1
4.6814	0.0107	0.8376	3.9245	0.0103	0.8927	2
4.4407	0.0114	0.8311	3.7252	0.0107	0.8775	3
4.2445	0.0119	0.8228	3.6283	0.0108	0.8695	4

Framework versions

Transformers 4.34.0.dev0
TensorFlow 2.13.0
Tokenizers 0.13.3