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sammy786/wav2vec2-xlsr-romansh_vallader

sourceHugging Faceapache-2.0updated 5y agoView on Hugging Face

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sammy786/wav2vec2-xlsr-romansh_vallader

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMONVOICE8_0 - rm-vallader dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):

—Loss: 30.31
—Wer: 26.32

Model description

"facebook/wav2vec2-xls-r-1b" was finetuned.

Intended uses & limitations

More information needed

Training and evaluation data

Training data - Common voice Finnish train.tsv, dev.tsv and other.tsv

Training procedure

For creating the train dataset, all possible datasets were appended and 90-10 split was used.

Training hyperparameters

The following hyperparameters were used during training:

—learning_rate: 0.000045637994662983496
—trainbatchsize: 16
—evalbatchsize: 16
—seed: 13
—gradientaccumulationsteps: 2
—totaltrainbatch_size: 32
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: cosinewithrestarts
—lrschedulerwarmup_steps: 500
—num_epochs: 40
—mixedprecisiontraining: Native AMP

Training results

Step	Training Loss	Validation Loss	Wer
200	5.895100	3.136624	0.999713
400	1.545700	0.445069	0.471584
600	0.693900	0.340700	0.363088
800	0.510600	0.295432	0.289610
1000	0.318800	0.286795	0.281860
1200	0.194000	0.307468	0.274110
1400	0.151800	0.304849	0.264351
1600	0.148300	0.303112	0.263203

Framework versions

—Transformers 4.16.0.dev0
—Pytorch 1.10.0+cu102
—Datasets 1.17.1.dev0
—Tokenizers 0.10.3

Evaluation Commands

1.To evaluate on mozilla-foundation/common_voice_8_0 with split test

bash

python eval.py --model_id sammy786/wav2vec2-xlsr-romansh_vallader --dataset mozilla-foundation/common_voice_8_0 --config rm-vallader --split test