model_result

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6132
• Accuracy: 0.9038

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:

• learning_rate: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.9231	3	1.6081	0.1538
No log	1.8462	6	1.5995	0.1731
No log	2.7692	9	1.5848	0.25
1.598	4.0	13	1.5500	0.3365
1.598	4.9231	16	1.5076	0.4904
1.598	5.8462	19	1.4453	0.6827
1.5052	6.7692	22	1.3662	0.6731
1.5052	8.0	26	1.2518	0.7212
1.5052	8.9231	29	1.1767	0.7308
1.2847	9.8462	32	1.1189	0.6923
1.2847	10.7692	35	1.0484	0.7596
1.2847	12.0	39	1.0011	0.7115
1.081	12.9231	42	0.9297	0.7692
1.081	13.8462	45	0.9014	0.7404
1.081	14.7692	48	0.8527	0.7692
0.9228	16.0	52	0.7915	0.8462
0.9228	16.9231	55	0.8105	0.75
0.9228	17.8462	58	0.7530	0.7885
0.7978	18.7692	61	0.7055	0.8558
0.7978	20.0	65	0.6827	0.8846
0.7978	20.9231	68	0.6725	0.8654
0.6996	21.8462	71	0.6646	0.875
0.6996	22.7692	74	0.6351	0.9038
0.6996	24.0	78	0.6202	0.9135
0.6471	24.9231	81	0.6186	0.9038
0.6471	25.8462	84	0.6157	0.8942
0.6471	26.7692	87	0.6148	0.8942
0.6172	27.6923	90	0.6132	0.9038

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1