sew-tiny-portuguese-cv7

lgris/sew-tiny-portuguese-cv7

sew-tiny-portuguese-cv7 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: sew
Access: Public
Created: Mar 2, 2022
Updated: Mar 23, 2022
SHA: 7a1ce3db

Datasets

mozilla-foundation/common_voice_7_0

Model card

From the Hugging Face model README

sew-tiny-portuguese-cv7

This model is a fine-tuned version of lgris/sew-tiny-pt on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 0.4232
Wer: 0.2745

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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	2.6	1000	1.0034	0.7308
4.1307	5.19	2000	0.6274	0.4721
4.1307	7.79	3000	0.5541	0.4130
1.3117	10.39	4000	0.5302	0.3880
1.3117	12.99	5000	0.5082	0.3644
1.2047	15.58	6000	0.4818	0.3539
1.2047	18.18	7000	0.4822	0.3477
1.14	20.78	8000	0.4781	0.3428
1.14	23.38	9000	0.4840	0.3401
1.0818	25.97	10000	0.4613	0.3251
1.0818	28.57	11000	0.4569	0.3257
1.0451	31.17	12000	0.4494	0.3132
1.0451	33.77	13000	0.4560	0.3201
1.011	36.36	14000	0.4687	0.3174
1.011	38.96	15000	0.4397	0.3122
0.9785	41.56	16000	0.4605	0.3173
0.9785	44.16	17000	0.4380	0.3064
0.9458	46.75	18000	0.4372	0.3048
0.9458	49.35	19000	0.4426	0.3039
0.9126	51.95	20000	0.4317	0.2962
0.9126	54.54	21000	0.4345	0.2960
0.8926	57.14	22000	0.4365	0.2948
0.8926	59.74	23000	0.4306	0.2940
0.8654	62.34	24000	0.4303	0.2928
0.8654	64.93	25000	0.4351	0.2915
0.8373	67.53	26000	0.4340	0.2909
0.8373	70.13	27000	0.4279	0.2907
0.83	72.73	28000	0.4214	0.2867
0.83	75.32	29000	0.4256	0.2849
0.8062	77.92	30000	0.4281	0.2826
0.8062	80.52	31000	0.4398	0.2865
0.7846	83.12	32000	0.4218	0.2812
0.7846	85.71	33000	0.4227	0.2791
0.7697	88.31	34000	0.4200	0.2767
0.7697	90.91	35000	0.4285	0.2791
0.7539	93.51	36000	0.4238	0.2777
0.7539	96.1	37000	0.4288	0.2757
0.7413	98.7	38000	0.4205	0.2748
0.7413	101.3	39000	0.4241	0.2761
0.7348	103.89	40000	0.4232	0.2745

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: sew
License: apache-2.0
Languages: pt
Created: Mar 2, 2022
Updated: Mar 23, 2022