whisper_final_nosp

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: 0.0732
• Train Accuracy: 0.0234
• Validation Loss: 0.8512
• Validation Accuracy: 0.0203
• Epoch: 24

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
7.5559	0.0010	6.3853	0.0013	0
6.3227	0.0021	5.7023	0.0038	1
4.9825	0.0063	3.6302	0.0109	2
2.9413	0.0126	2.1959	0.0154	3
1.9349	0.0157	1.6630	0.0172	4
1.4741	0.0171	1.3813	0.0181	5
1.1975	0.0181	1.2161	0.0186	6
1.0048	0.0188	1.0990	0.0191	7
0.8598	0.0194	1.0165	0.0194	8
0.7431	0.0199	0.9603	0.0196	9
0.6489	0.0203	0.9106	0.0198	10
0.5682	0.0207	0.8787	0.0199	11
0.4985	0.0210	0.8548	0.0200	12
0.4372	0.0213	0.8352	0.0201	13
0.3829	0.0216	0.8190	0.0202	14
0.3327	0.0219	0.8148	0.0202	15
0.2904	0.0221	0.8139	0.0202	16
0.2492	0.0224	0.8188	0.0202	17
0.2140	0.0226	0.8146	0.0203	18
0.1825	0.0228	0.8115	0.0203	19
0.1538	0.0229	0.8228	0.0203	20
0.1293	0.0231	0.8341	0.0202	21
0.1070	0.0232	0.8404	0.0202	22
0.0889	0.0233	0.8569	0.0202	23
0.0732	0.0234	0.8512	0.0203	24

Framework versions

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