unlearn_speech_commands_wav2vec2-base_neggrad_10_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_speech_commands_wav2vec2-base_neggrad_10_42

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

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superb_ks_42

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

Loss: -10.0405
Accuracy: 0.6209
Test Accuracy: 0.6209
Df Accuracy: 0.1405
Unlearn Overall Accuracy: 0.7402
Unlearn Time: 556.1764

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: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	160	-10.0405	0.1405	0.7402	0.7402	-1
No log	2.0	320	-26.6717	0.1405	0.7402	0.7402	-1
No log	3.0	480	-48.1647	0.1405	0.7402	0.7402	-1
No log	4.0	640	-72.2596	0.1405	0.7402	0.7402	-1
No log	5.0	800	-96.7467	0.1405	0.7402	0.7402	-1
No log	6.0	960	-119.6291	0.1405	0.7402	0.7402	-1
-122.3648	7.0	1120	-139.2895	0.1405	0.7402	0.7402	-1
-122.3648	8.0	1280	-154.3732	0.1405	0.7402	0.7402	-1
-122.3648	9.0	1440	-163.8446	0.1405	0.7402	0.7402	-1
-122.3648	10.0	1600	-167.0999	0.1405	0.7402	0.7402	-1

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2