You can deploy this model and start earning money today!

MatsRooth/
wav2vec2_prosodic_minimal

Name: wav2vec2_prosodic_minimal
Availability: InStock

safetensors

wav2vec2

audio-classification

generated_from_trainer

facebook/wav2vec2-base

finetune

apache-2.0

Views

No views yet

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

MatsRooth/wav2vec2_prosodic_minimal

wav2vec2_prosodic_minimal

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MatsRooth/
wav2vec2_prosodic_minimal