IDAT_grn_aug_898_copy_Wav2Vec

alirzb/IDAT_grn_aug_898_copy_Wav2Vec

IDAT_grn_aug_898_copy_Wav2Vec is a machine learning model from alirzb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

39% of all-time downloads

All-time downloads

Public

Repo size

3.8 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin378 MB · 100%

At a glance

License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Sep 12, 2024
Updated: Sep 12, 2024
SHA: 4f45b935

Base models

facebook/wav2vec2-base

Model card

From the Hugging Face model README

IDAT_grn_aug_898_copy_Wav2Vec

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5824
Accuracy: 0.7625

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: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6513	1.0	100	0.5871	0.67
0.6895	2.0	200	0.6970	0.5
0.6715	3.0	300	0.7229	0.5
0.531	4.0	400	0.7113	0.5
0.6903	5.0	500	0.6826	0.585
0.4481	6.0	600	0.6685	0.635
0.5603	7.0	700	0.8770	0.485
0.4866	8.0	800	0.3783	0.9025
0.5095	9.0	900	0.5246	0.8175
0.1992	10.0	1000	0.5824	0.7625

Framework versions

Transformers 4.32.1
Pytorch 2.1.2
Datasets 2.16.1
Tokenizers 0.13.3

Type: wav2vec2
License: apache-2.0
Created: Sep 12, 2024
Updated: Sep 12, 2024