wav2vec2-minds14-audio-classification-en

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

• Loss: 2.6639
• Accuracy: 0.0796

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	3	2.6727	0.0531
No log	1.8667	7	2.6503	0.0531
2.6417	2.9333	11	2.6485	0.0796
2.6417	4.0	15	2.6514	0.0531
2.6417	4.8	18	2.6531	0.0442
2.6189	5.8667	22	2.6596	0.0619
2.6189	6.9333	26	2.6650	0.0531
2.6123	8.0	30	2.6639	0.0796

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1