microsoft-wavlm-fleurs-ur

akmalmasud96/microsoft-wavlm-fleurs-ur

microsoft-wavlm-fleurs-ur is a automatic speech recognition model from akmalmasud96. Use it when you need speech turned into text. It is set up for transformers.

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

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At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: wavlm
Access: Public
Created: Feb 5, 2023
Updated: Feb 5, 2023
SHA: ad9f3516

Datasets

fleurs

Model card

From the Hugging Face model README

microsoft-wavlm-fleurs-ur

This model is a fine-tuned version of microsoft/wavlm-large on the fleurs dataset. It achieves the following results on the evaluation set:

Loss: 0.7294
Wer: 0.4026

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: 0.0003
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 8
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 15.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.911	0.35	100	3.7784	1.0
3.0833	0.71	200	3.0964	1.0
3.028	1.06	300	3.0377	1.0
2.5114	1.41	400	2.4941	0.9922
1.0583	1.77	500	1.0753	0.7579
0.715	2.12	600	0.8524	0.6410
0.6779	2.47	700	0.7711	0.6063
0.6123	2.83	800	0.7170	0.5706
0.8183	3.18	900	0.6897	0.5368
0.5195	3.53	1000	0.6586	0.5303
0.4774	3.89	1100	0.6306	0.5014
0.4242	4.24	1200	0.6138	0.4817
0.4549	4.59	1300	0.6027	0.4678
0.2576	4.95	1400	0.5878	0.4600
0.1578	5.3	1500	0.6144	0.4585
0.3556	5.65	1600	0.5884	0.4582
0.2427	6.01	1700	0.6071	0.4572
0.267	6.36	1800	0.6303	0.4514
0.2468	6.71	1900	0.6358	0.4495
0.159	7.07	2000	0.6242	0.4312
0.1527	7.42	2100	0.6372	0.4400
0.1401	7.77	2200	0.6252	0.4292
0.1211	8.13	2300	0.6358	0.4251
0.1022	8.48	2400	0.6529	0.4356
0.0818	8.83	2500	0.6773	0.4200
0.0918	9.19	2600	0.6879	0.4267
0.119	9.54	2700	0.6948	0.4254
0.1615	9.89	2800	0.6920	0.4259
0.0953	10.25	2900	0.7019	0.4218
0.1008	10.6	3000	0.6933	0.4133
0.0729	10.95	3100	0.6950	0.4164
0.0636	11.31	3200	0.7151	0.4121
0.0395	11.66	3300	0.7053	0.4098
0.0391	12.01	3400	0.7081	0.3984
0.0507	12.37	3500	0.7012	0.4111
0.0598	12.72	3600	0.7169	0.4035
0.0515	13.07	3700	0.7358	0.4102
0.0429	13.43	3800	0.7236	0.4013
0.0398	13.78	3900	0.7404	0.4026
0.0946	14.13	4000	0.7285	0.4029
0.0428	14.49	4100	0.7271	0.3991
0.0329	14.84	4200	0.7294	0.4026

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1
Datasets 2.8.0
Tokenizers 0.13.2

Task: Automatic Speech Recognition
Library: transformers
Type: wavlm
Created: Feb 5, 2023
Updated: Feb 5, 2023