wav2vec2_prosodic_minimal

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

• Loss: 0.1205
• Accuracy: 0.9802

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: 4
• eval_batch_size: 4
• seed: 0
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3769	1.0	2151	0.2877	0.9318
0.4347	2.0	4302	0.1720	0.9608
0.3185	3.0	6453	0.1805	0.9625
0.3362	4.0	8604	0.1409	0.9720
0.2105	5.0	10755	0.1173	0.9753
0.2106	6.0	12906	0.1460	0.9733
0.1819	7.0	15057	0.1431	0.9743
0.2946	8.0	17208	0.1245	0.9766
0.0416	9.0	19359	0.1241	0.9786
0.1006	10.0	21510	0.1205	0.9802

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 2.9.0+cu128
• Datasets 2.13.1
• Tokenizers 0.15.0