wav2vec2-minds14-audio-classification-all

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: 2.6367
• Accuracy: 0.0973

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
2.6374	0.9951	51	2.6375	0.0894
2.6347	1.9902	102	2.6334	0.0900
2.6352	2.9854	153	2.6323	0.0930
2.6282	4.0	205	2.6280	0.0924
2.6224	4.9951	256	2.6398	0.0894
2.6122	5.9902	307	2.6306	0.0912
2.6225	6.9854	358	2.6325	0.0906
2.6196	8.0	410	2.6358	0.0961
2.6154	8.9951	461	2.6357	0.0924
2.6028	9.9512	510	2.6367	0.0973

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1