asd_pron_w2v_reg_balanced_500_79_corr_converse

slplab/asd_pron_w2v_reg_balanced_500_79_corr_converse

asd_pron_w2v_reg_balanced_500_79_corr_converse is a machine learning model from slplab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Sep 15, 2023
Updated: Sep 17, 2023
SHA: b6d4d1a9

Model card

From the Hugging Face model README

asd_pron_w2v_reg_balanced_500_79_corr_converse

This model is a fine-tuned version of slplab/wav2vec2-xls-r-300m_phone-mfa_korean on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5163
Spearman Correlation: 0.1648

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Spearman Correlation
0.5482	1.0	308	0.5296	0.0806
0.3928	2.0	616	0.5051	0.1624
0.3876	3.0	924	0.5314	0.2300
0.3913	4.0	1232	0.5007	0.2124
0.3896	5.0	1540	0.5150	0.1451
0.3894	6.0	1848	0.5103	0.1414
0.3896	7.0	2156	0.5173	0.2652
0.3909	8.0	2464	0.5151	0.2192
0.3875	9.0	2772	0.5093	0.1937
0.3873	10.0	3080	0.5134	0.1517
0.3938	11.0	3388	0.5084	0.3055
0.3894	12.0	3696	0.5025	0.1990
0.3907	13.0	4004	0.5249	0.2072
0.389	14.0	4312	0.5157	0.2459
0.3887	15.0	4620	0.5033	0.2882
0.3882	16.0	4928	0.5078	0.2449
0.3906	17.0	5236	0.5215	0.2655
0.3903	18.0	5544	0.5101	0.2863
0.3905	19.0	5852	0.5090	0.2158
0.3877	20.0	6160	0.5226	0.1800
0.3874	21.0	6468	0.5123	0.2398
0.3901	22.0	6776	0.5108	0.2126
0.3913	23.0	7084	0.5195	0.1674
0.3857	24.0	7392	0.5099	0.2044
0.387	25.0	7700	0.5174	0.2156
0.3878	26.0	8008	0.5202	0.1925
0.3877	27.0	8316	0.5119	0.1712
0.389	28.0	8624	0.5172	0.1732
0.3909	29.0	8932	0.5195	0.1783
0.3876	30.0	9240	0.5163	0.1648

Framework versions

Transformers 4.13.0
Pytorch 2.0.0+cu118
Datasets 2.14.4
Tokenizers 0.10.3

Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Sep 15, 2023
Updated: Sep 17, 2023