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w2v-bert-2.0-ukrainian-colab-CV16.0 – AI Model by Oysiyl | AlphaNeural AI
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Oysiyl
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w2v-bert-2.0-ukrainian-colab-CV16.0
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
uk
mozilla-foundation/common_voice_16_1
ylacombe/w2v-bert-2.0
finetune
mit
model-index
endpoints_compatible
us
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w2v-bert-2.0-ukrainian-colab-CV16.0
This model is a fine-tuned version of
ylacombe/w2v-bert-2.0
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1438
Wer: 0.0987
Note: the model was finetuned on Ukrainian alphabet in lowercase plus "'" sign. Therefore this model can't add punctuation or capitalization.
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: 64
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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
1.0371
1.98
525
0.1509
0.1498
0.0728
3.96
1050
0.1256
0.1279
0.0382
5.94
1575
0.1260
0.1041
0.0213
7.92
2100
0.1333
0.0997
0.0118
9.91
2625
0.1438
0.0987
Framework versions
Transformers 4.37.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.15.1
