hubert-classifier – AI Model by fydhfzh | AlphaNeural AI

You can deploy this model and start earning money today!

fydhfzh/
hubert-classifier

like

0

audio-classification

generated_from_trainer

facebook/hubert-base-ls960

endpoints_compatible

Views

No views yet

hubert-classifier

This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.9330
Accuracy: 0.0674
Precision: 0.0116
Recall: 0.0674
F1: 0.0182
Binary: 0.3423

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: 1e-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	4.4099	0.0647	0.0191	0.0647	0.0221	0.2396
No log	1.91	100	4.3523	0.0593	0.0190	0.0593	0.0194	0.3019
No log	2.87	150	4.2416	0.0701	0.0246	0.0701	0.0235	0.3358
No log	3.83	200	4.1412	0.0701	0.0265	0.0701	0.0214	0.3437
No log	4.78	250	4.0716	0.0593	0.0069	0.0593	0.0122	0.3334
No log	5.74	300	4.0195	0.0701	0.0124	0.0701	0.0186	0.3453
No log	6.7	350	3.9850	0.0593	0.0073	0.0593	0.0126	0.3350
No log	7.66	400	3.9610	0.0647	0.0097	0.0647	0.0162	0.3388
No log	8.61	450	3.9420	0.0674	0.0113	0.0674	0.0180	0.3396
4.2019	9.57	500	3.9330	0.0674	0.0116	0.0674	0.0182	0.3423

Framework versions

Transformers 4.38.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1