Modelpublic

bigmorning/whisper_input_decoder_shift_r_labels_with_force__0020

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

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Model Card

whisperinputdecodershiftrlabelswithforce_0020

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: 2.8149
—Train Accuracy: 0.0170
—Train Wermet: 0.6022
—Validation Loss: 2.7020
—Validation Accuracy: 0.0136
—Validation Wermet: 0.6811
—Epoch: 19

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', 'learningrate': 1e-05, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weightdecay_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
3.6006	0.0138	0.7421	3.2581	0.0117	0.8120	10
3.5300	0.0140	0.7296	3.2415	0.0118	0.8257	11
3.4554	0.0143	0.7179	3.2163	0.0119	0.8078	12
3.3930	0.0145	0.7057	3.1612	0.0121	0.7758	13
3.3218	0.0148	0.6946	3.1357	0.0122	0.7760	14
3.2424	0.0151	0.6806	3.0812	0.0123	0.7639	15
3.1577	0.0155	0.6633	3.0193	0.0126	0.7428	16
3.0655	0.0159	0.6454	2.9643	0.0128	0.7423	17
2.9579	0.0164	0.6271	2.8510	0.0132	0.7103	18
2.8149	0.0170	0.6022	2.7020	0.0136	0.6811	19

Framework versions

—Transformers 4.34.0.dev0
—TensorFlow 2.13.0
—Tokenizers 0.13.3