whisper_input_decoder_shift_r_labels_with_force__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: 3.6763
• Train Accuracy: 0.0136
• Train Wermet: 0.7543
• Validation Loss: 3.3183
• Validation Accuracy: 0.0116
• Validation Wermet: 0.8678
• 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': 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
4.0889	0.0123	0.8067	3.5310	0.0110	0.8916	5
3.9575	0.0127	0.7908	3.4478	0.0113	0.8407	6
3.8547	0.0130	0.7781	3.4227	0.0113	0.8670	7
3.7599	0.0133	0.7654	3.3519	0.0115	0.8375	8
3.6763	0.0136	0.7543	3.3183	0.0116	0.8678	9

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3