audio_classification

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 2.6820
• Accuracy: 0.0708

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	3	2.6643	0.0708
No log	1.8	6	2.6708	0.0796
No log	2.8	9	2.6663	0.0708
2.9728	3.8	12	2.6744	0.0885
2.9728	4.8	15	2.6724	0.0796
2.9728	5.8	18	2.6768	0.0796
2.9551	6.8	21	2.6797	0.0708
2.9551	7.8	24	2.6818	0.0708
2.9551	8.8	27	2.6821	0.0708
2.9439	9.8	30	2.6820	0.0708

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1
• Datasets 3.3.2
• Tokenizers 0.21.0