wolof – AI Model by baayematar | AlphaNeural AI

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baayematar/
wolof

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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wolof

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

Loss: 0.3554
Wer: 0.3717

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: 3
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.9163	0.75	1000	1.0340	0.8431
0.77	1.5	2000	0.4280	0.5549
0.544	2.25	3000	0.3612	0.4818
0.4548	3.0	4000	0.3530	0.4606
0.3662	3.75	5000	0.3296	0.4422
0.3168	4.5	6000	0.3323	0.4303
0.2651	5.25	7000	0.3133	0.4092
0.2276	6.0	8000	0.3257	0.4073
0.1815	6.75	9000	0.3199	0.3861
0.1583	7.5	10000	0.3268	0.38
0.1313	8.25	11000	0.3505	0.3782
0.1156	9.0	12000	0.3571	0.3763
0.1032	9.75	13000	0.3554	0.3717

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3