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w2v-bert-2.0-dutch-colab-CV16.0 – AI Model by Oysiyl | AlphaNeural AI
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w2v-bert-2.0-dutch-colab-CV16.0
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
ylacombe/w2v-bert-2.0
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endpoints_compatible
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w2v-bert-2.0-dutch-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: 0.0920
Wer: 0.0573
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: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.3106
1.0
358
0.1833
0.1350
0.0924
2.0
716
0.1365
0.0932
0.0521
3.0
1074
0.1121
0.0732
0.033
3.99
1432
0.0957
0.0619
0.0221
4.99
1790
0.0920
0.0573
Framework versions
Transformers 4.37.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.15.2
