wav2vec2-finetuned-wolofdata2 – AI Model by mohamedlamine | AlphaNeural AI

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mohamedlamine/
wav2vec2-finetuned-wolofdata2

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automatic-speech-recognition

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wav2vec2-finetuned-wolofdata2

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: 0.1969
Wer: 0.1897

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: 300
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
12.9468	0.75	100	4.0058	1.0
3.3471	1.49	200	3.1350	1.0
3.014	2.24	300	2.4949	0.9997
1.5935	2.99	400	0.8807	0.72
0.7567	3.73	500	0.4770	0.47
0.4514	4.48	600	0.3082	0.3003
0.2778	5.22	700	0.2297	0.2244
0.2062	5.97	800	0.1969	0.1897

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.10.3