wav2vec2-cer-extension – AI Model by adrianSauer | AlphaNeural AI

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adrianSauer/
wav2vec2-cer-extension

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_16_1

glob-asr/wav2vec2-large-xls-r-300m-guarani-small

endpoints_compatible

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Common Voice 16

This model is a fine-tuned version of glob-asr/wav2vec2-large-xls-r-300m-guarani-small on the Common Voice 16 dataset. It achieves the following results on the evaluation set:

Loss: 0.2425
Cer: 5.9170

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: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 3000
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
1.2573	0.4955	500	0.3703	8.4904
0.9205	0.9911	1000	0.3224	7.6296
0.7466	1.4866	1500	0.2938	7.1221
0.6766	1.9822	2000	0.2715	6.6510
0.5782	2.4777	2500	0.2831	7.0497
0.5495	2.9732	3000	0.2425	5.9170

Framework versions

Transformers 4.44.1
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1