Arousal-wav2vec2-base-EMOPIA

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: 0.4207
• Accuracy: 0.9014

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: 1e-06
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 3
• total_train_batch_size: 3
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6871	1.0	269	0.6601	0.6761
0.6071	2.0	538	0.5375	0.8451
0.4312	3.0	807	0.3544	0.8873
0.306	4.0	1076	0.3780	0.8592
0.3052	5.0	1345	0.4133	0.8873
0.3099	6.0	1614	0.4112	0.8873
0.2965	7.0	1883	0.4241	0.8873
0.2954	8.0	2152	0.4381	0.8873
0.2905	9.0	2421	0.4294	0.9014
0.2868	10.0	2690	0.4208	0.9014
0.284	11.0	2959	0.4077	0.9014
0.2666	12.0	3228	0.4149	0.9014
0.2697	13.0	3497	0.4108	0.9014
0.2622	14.0	3766	0.4187	0.9014
0.2648	15.0	4035	0.4207	0.9014

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1