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w2v-bert-2.0-mongolian-colab-CV16.0 – AI Model by mehedihasanbijoy | AlphaNeural AI
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w2v-bert-2.0-mongolian-colab-CV16.0
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
common_voice_16_0
facebook/w2v-bert-2.0
finetune
mit
model-index
endpoints_compatible
us
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w2v-bert-2.0-mongolian-colab-CV16.0
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
Loss: 0.6866
Wer: 0.5183
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: 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: 500
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.8436
5.2174
300
0.6866
0.5183
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1
