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w2v-bert-2.0-mongolian-finetuned – AI Model by mhlongoke91 | AlphaNeural AI

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mhlongoke91/
w2v-bert-2.0-mongolian-finetuned

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automatic-speech-recognition

generated_from_trainer

facebook/w2v-bert-2.0

endpoints_compatible

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w2v-bert-2.0-mongolian-finetuned

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: 628.7474
Wer: 13.0

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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 30
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.51.2
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.21.1