wav2vec2-xls-r-ewe-20-hours – AI Model by asr-africa | AlphaNeural AI

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asr-africa/
wav2vec2-xls-r-ewe-20-hours

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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wav2vec2-xls-r-ewe-20-hours

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

Loss: 0.7162
Wer: 0.3681
Cer: 0.1051

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: 0.0003
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.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_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
8.2538	8.4034	500	0.5225	0.4745	0.1342
0.8974	16.8067	1000	0.4220	0.3655	0.1072
0.5528	25.2101	1500	0.5054	0.3678	0.1054
0.3461	33.6134	2000	0.6326	0.3765	0.1080
0.2328	42.0168	2500	0.7162	0.3681	0.1051

Framework versions

Transformers 4.46.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3