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MatsRooth/
wav2vec2-present

Name: wav2vec2-present
Rating: 2.5 (12 reviews)

safetensors

wav2vec2

audio-classification

generated_from_trainer

facebook/wav2vec2-base

finetune

apache-2.0

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wav2vec2-present

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: 0.1188
Accuracy: 0.9783

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
0.5859	1.0	2151	0.2952	0.9351
0.4323	2.0	4302	0.2043	0.9562
0.4494	3.0	6453	0.1691	0.9644
0.0351	4.0	8604	0.1447	0.9677
0.2679	5.0	10755	0.1372	0.9704
0.3252	6.0	12906	0.1281	0.9720
0.1319	7.0	15057	0.1087	0.9789
0.0646	8.0	17208	0.1371	0.9740
0.1035	9.0	19359	0.1219	0.9776
0.1148	10.0	21510	0.1188	0.9783

Framework versions

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

MatsRooth/wav2vec2-present

wav2vec2-present

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MatsRooth/
wav2vec2-present