whisper_werbest

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: 0.3071
• Train Accuracy: 0.0324
• Train Wermet: 1.7931
• Validation Loss: 0.5766
• Validation Accuracy: 0.0312
• Validation Wermet: 1.5663
• Epoch: 14

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
5.0795	0.0116	43.8776	4.4395	0.0122	35.4119	0
4.3059	0.0131	29.7976	4.0311	0.0143	26.0070	1
3.8871	0.0148	19.3999	3.6500	0.0158	19.2186	2
3.0943	0.0184	18.3704	2.3327	0.0226	22.5034	3
1.8954	0.0240	16.2471	1.4889	0.0266	14.2782	4
1.2781	0.0269	8.4169	1.1273	0.0283	7.4581	5
0.9797	0.0283	4.8739	0.9481	0.0292	3.9451	6
0.8006	0.0293	2.7433	0.8371	0.0297	2.3065	7
0.6764	0.0299	2.1646	0.7554	0.0301	1.3005	8
0.5820	0.0305	1.5323	0.6980	0.0305	1.1238	9
0.5078	0.0310	1.4328	0.6617	0.0306	1.2793	10
0.4455	0.0314	1.4891	0.6252	0.0309	1.6833	11
0.3927	0.0317	1.6700	0.6123	0.0310	2.1091	12
0.3473	0.0321	1.6245	0.5851	0.0311	1.4109	13
0.3071	0.0324	1.7931	0.5766	0.0312	1.5663	14

Framework versions

• Transformers 4.25.0.dev0
• TensorFlow 2.9.2
• Datasets 2.6.1
• Tokenizers 0.13.2