wav2vec2-large-xls-r-300m-sw-10hr-v1 – AI Model by KasuleTrevor | AlphaNeural AI

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KasuleTrevor/
wav2vec2-large-xls-r-300m-sw-10hr-v1

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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wav2vec2-large-xls-r-300m-sw-10hr-v1

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: 0.3209
Wer: 0.2402
Cer: 0.0623

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: 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: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
5.1124	0.9732	200	2.8417	1.0	1.0
1.3729	1.9465	400	0.5626	0.5369	0.1395
0.4189	2.9197	600	0.3993	0.4045	0.1012
0.2836	3.8929	800	0.3492	0.3428	0.0863
0.202	4.8662	1000	0.3426	0.3230	0.0812
0.1529	5.8394	1200	0.3318	0.2909	0.0739
0.1171	6.8127	1400	0.3149	0.2759	0.0710
0.0957	7.7859	1600	0.3239	0.2641	0.0681
0.0761	8.7591	1800	0.3383	0.2548	0.0658
0.0639	9.7324	2000	0.3204	0.2398	0.0624

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1