WavLM-large-CORAA-pt

lgris/WavLM-large-CORAA-pt

WavLM-large-CORAA-pt is a automatic speech recognition model from lgris. Use it when you need speech turned into text. 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

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wavlm
Access: Public
Created: Mar 2, 2022
Updated: Feb 10, 2022
SHA: b9363767

Model card

From the Hugging Face model README

WavLM-large-CORAA-pt

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

Loss: 0.6144
Wer: 0.3840

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 40000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.04	1000	1.9230	0.9960
5.153	0.08	2000	1.3733	0.8444
5.153	0.13	3000	1.1992	0.7362
1.367	0.17	4000	1.1289	0.6957
1.367	0.21	5000	1.0357	0.6470
1.1824	0.25	6000	1.0216	0.6201
1.1824	0.29	7000	0.9338	0.6036
1.097	0.33	8000	0.9149	0.5760
1.097	0.38	9000	0.8885	0.5541
1.0254	0.42	10000	0.8678	0.5366
1.0254	0.46	11000	0.8349	0.5323
0.9782	0.5	12000	0.8230	0.5155
0.9782	0.54	13000	0.8245	0.5049
0.9448	0.59	14000	0.7802	0.4990
0.9448	0.63	15000	0.7650	0.4900
0.9092	0.67	16000	0.7665	0.4796
0.9092	0.71	17000	0.7568	0.4795
0.8764	0.75	18000	0.7403	0.4615
0.8764	0.8	19000	0.7219	0.4644
0.8498	0.84	20000	0.7180	0.4502
0.8498	0.88	21000	0.7017	0.4436
0.8278	0.92	22000	0.6992	0.4395
0.8278	0.96	23000	0.7021	0.4329
0.8077	1.0	24000	0.6892	0.4265
0.8077	1.05	25000	0.6940	0.4248
0.7486	1.09	26000	0.6767	0.4202
0.7486	1.13	27000	0.6734	0.4150
0.7459	1.17	28000	0.6650	0.4152
0.7459	1.21	29000	0.6559	0.4078
0.7304	1.26	30000	0.6536	0.4088
0.7304	1.3	31000	0.6537	0.4025
0.7183	1.34	32000	0.6462	0.4008
0.7183	1.38	33000	0.6381	0.3973
0.7059	1.42	34000	0.6266	0.3930
0.7059	1.46	35000	0.6280	0.3921
0.6983	1.51	36000	0.6248	0.3897
0.6983	1.55	37000	0.6275	0.3872
0.6892	1.59	38000	0.6199	0.3852
0.6892	1.63	39000	0.6180	0.3842
0.691	1.67	40000	0.6144	0.3840

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.11.0

Task: Automatic Speech Recognition
Library: transformers
Type: wavlm
License: apache-2.0
Languages: pt
Created: Mar 2, 2022
Updated: Feb 10, 2022