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rah_toki_pona – AI Model by pabagcha | AlphaNeural AI
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rah_toki_pona
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
common_voice_11_0
model-index
endpoints_compatible
us
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rah_toki_pona
This model was finetuned from facebook/wav2vec2-xls-r-300m on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
Loss: 0.1053
Wer: 0.0640
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
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: 15
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0516
3.22
400
0.1301
0.0996
0.0817
6.45
800
0.1319
0.0899
0.0567
9.67
1200
0.1009
0.0682
0.0376
12.9
1600
0.1053
0.0640
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
