wav2vec2-classifier – AI Model by fydhfzh | AlphaNeural AI

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fydhfzh/
wav2vec2-classifier

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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wav2vec2-classifier

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

Loss: 3.0684
Accuracy: 0.4474
Precision: 0.3646
Recall: 0.4474
F1: 0.3683
Binary: 0.6094

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
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Binary
No log	0.96	50	4.2611	0.0647	0.0196	0.0647	0.0252	0.3121
4.403	1.91	100	3.9746	0.0889	0.0305	0.0889	0.0343	0.3509
4.1379	2.87	150	3.7561	0.1698	0.0733	0.1698	0.0880	0.4135
3.8988	3.83	200	3.5600	0.2372	0.1619	0.2372	0.1527	0.4652
3.6407	4.78	250	3.4072	0.3019	0.2248	0.3019	0.2174	0.5100
3.5551	5.74	300	3.2951	0.3720	0.2851	0.3720	0.2858	0.5555
3.4319	6.7	350	3.2052	0.4070	0.3239	0.4070	0.3214	0.5803
3.3287	7.66	400	3.1429	0.4151	0.3738	0.4151	0.3421	0.5868
3.1949	8.61	450	3.0862	0.4555	0.3707	0.4555	0.3759	0.6178
3.2056	9.57	500	3.0684	0.4474	0.3646	0.4474	0.3683	0.6094

Framework versions

Transformers 4.38.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1