whisper_end22

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: 0.1061
• Train Accuracy: 0.0341
• Validation Loss: 0.5635
• Validation Accuracy: 0.0314
• Epoch: 22

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	Validation Loss	Validation Accuracy	Epoch
5.0856	0.0116	4.4440	0.0123	0
4.3149	0.0131	4.0521	0.0142	1
3.9260	0.0146	3.7264	0.0153	2
3.5418	0.0160	3.3026	0.0174	3
2.7510	0.0198	2.0157	0.0241	4
1.6782	0.0250	1.3567	0.0273	5
1.1705	0.0274	1.0678	0.0286	6
0.9126	0.0287	0.9152	0.0294	7
0.7514	0.0296	0.8057	0.0299	8
0.6371	0.0302	0.7409	0.0302	9
0.5498	0.0307	0.6854	0.0306	10
0.4804	0.0312	0.6518	0.0307	11
0.4214	0.0316	0.6200	0.0310	12
0.3713	0.0319	0.5947	0.0311	13
0.3281	0.0322	0.5841	0.0311	14
0.2891	0.0325	0.5700	0.0313	15
0.2550	0.0328	0.5614	0.0313	16
0.2237	0.0331	0.5572	0.0313	17
0.1959	0.0333	0.5563	0.0314	18
0.1698	0.0335	0.5530	0.0314	19
0.1455	0.0337	0.5590	0.0314	20
0.1242	0.0339	0.5743	0.0313	21
0.1061	0.0341	0.5635	0.0314	22

Framework versions

• Transformers 4.25.0.dev0
• TensorFlow 2.9.2
• Tokenizers 0.13.2