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Leonel-Maia/
Wav2vec2-fula

Name: Wav2vec2-fula
Availability: InStock

transformers

safetensors

wav2vec2

automatic-speech-recognition

LAfricaMobile/fulfulde

generated_from_trainer

facebook/wav2vec2-xls-r-300m

finetune

apache-2.0

endpoints_compatible

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Wav2vec2-fula

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the LAFRICAMOBILE/FULFULDE - DEFAULT dataset. It achieves the following results on the evaluation set:

Loss: 0.3143
Wer: 0.5455

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 60.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.1344	0.3437	500	3.0935	1.0
0.7323	0.6874	1000	0.6304	0.7120
0.5416	1.0316	1500	0.4785	0.6491
0.4479	1.3753	2000	0.4202	0.6207
0.4541	1.7190	2500	0.3851	0.6006
0.365	2.0632	3000	0.3701	0.5885
0.3433	2.4069	3500	0.3648	0.5797
0.3561	2.7506	4000	0.3438	0.5716
0.3237	3.0949	4500	0.3647	0.5677
0.322	3.4386	5000	0.3427	0.5638
0.2921	3.7823	5500	0.3345	0.5604
0.3037	4.1265	6000	0.3352	0.5541
0.2695	4.4702	6500	0.3202	0.5515
0.2804	4.8139	7000	0.3353	0.5525
0.2908	5.1581	7500	0.3384	0.5485
0.2646	5.5018	8000	0.3164	0.5462
0.2982	5.8455	8500	0.3143	0.5455
0.2978	6.1897	9000	0.3218	0.5424
0.288	6.5334	9500	0.3152	0.5418
0.2706	6.8771	10000	0.3211	0.5398
0.3008	7.2213	10500	0.3266	0.5398
0.2674	7.5650	11000	0.3185	0.5379

Framework versions

Transformers 4.50.3
Pytorch 2.7.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1

Leonel-Maia/Wav2vec2-fula

Wav2vec2-fula

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Leonel-Maia/
Wav2vec2-fula