whisper_input_decoder_equal_labels_no_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: 0.0004
• Train Accuracy: 0.0362
• Train Wermet: 16.8461
• Validation Loss: 0.0004
• Validation Accuracy: 0.0266
• Validation Wermet: 34.1220
• 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
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
0.0013	0.0362	21.5445	0.0010	0.0266	42.3508	5
0.0009	0.0362	20.2775	0.0008	0.0266	40.4061	6
0.0007	0.0362	19.5082	0.0006	0.0266	38.2329	7
0.0005	0.0362	17.9967	0.0005	0.0266	35.9761	8
0.0004	0.0362	16.8461	0.0004	0.0266	34.1220	9

Framework versions

• Transformers 4.33.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3