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Kumaoni-Bhojpuri1h-per-lang-w2v-bert-2.0 – AI Model by dhasmana | AlphaNeural AI
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dhasmana
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Kumaoni-Bhojpuri1h-per-lang-w2v-bert-2.0
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transformers
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
facebook/w2v-bert-2.0
finetune
mit
endpoints_compatible
us
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Kumaoni-Bhojpuri1h-per-lang-w2v-bert-2.0
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0351
Cer: 0.2155
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
Cer
4.1245
7.1429
300
1.0351
0.2155
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
