wavlm-basic_s-f-o_8batch_10sec_0.0001lr_unfrozen

This model is a fine-tuned version of microsoft/wavlm-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2366
• Accuracy: 0.8
• F1: 0.7957

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.003
• num_epochs: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
2.2461	1.0	131	2.0275	0.4667	0.3795
1.1331	2.0	262	0.9031	0.7833	0.7681
0.7081	2.99	393	0.4658	0.85	0.8344
0.4829	4.0	525	0.6289	0.8333	0.8257
0.2998	5.0	656	0.6962	0.8333	0.8257
0.1818	6.0	787	0.5314	0.8667	0.8745
0.168	6.99	918	0.6366	0.8667	0.8666
0.1822	8.0	1050	0.5684	0.8667	0.8621
0.1178	9.0	1181	0.5222	0.8833	0.8834
0.1731	10.0	1312	0.8176	0.85	0.8430
0.1967	10.99	1443	0.9820	0.8	0.7935
0.0788	12.0	1575	0.5773	0.8667	0.8655

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3