unlearn_speech_commands_whisper-base_neggrad_8_42 – AI Model by jialicheng | AlphaNeural AI

You can deploy this model and start earning money today!

jialicheng/
unlearn_speech_commands_whisper-base_neggrad_8_42

like

0

audio-classification

generated_from_trainer

openai/whisper-base

Views

No views yet

superb_ks_42

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

Loss: -12.8314
Accuracy: 0.6209
Test Accuracy: 0.6209
Df Accuracy: 0.1395
Unlearn Overall Accuracy: 0.7407
Unlearn Time: 1563.4179

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	128	-12.8314	0.1395	0.7407	0.7407	-1
No log	2.0	256	-42.8635	0.1395	0.7407	0.7407	-1
No log	3.0	384	-79.2461	0.1395	0.7407	0.7407	-1
No log	4.0	512	-117.8021	0.1395	0.7407	0.7407	-1
No log	5.0	640	-155.4660	0.1395	0.7407	0.7407	-1
No log	6.0	768	-189.7714	0.1395	0.7407	0.7407	-1
No log	7.0	896	-218.6319	0.1395	0.7407	0.7407	-1
-258.1476	8.0	1024	-240.4217	0.1395	0.7407	0.7407	-1
-258.1476	9.0	1152	-253.9992	0.1395	0.7407	0.7407	-1
-258.1476	10.0	1280	-258.6347	0.1395	0.7407	0.7407	-1

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2