README.md

metadata

base_model: facebook/w2v-bert-2.0
datasets:
  - common_voice_16_0
library_name: transformers
license: mit
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: w2v-bert-2.0-mongolian-colab-CV16.0
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: common_voice_16_0
          type: common_voice_16_0
          config: mn
          split: test
          args: mn
        metrics:
          - type: wer
            value: 0.5182727865999565
            name: Wer

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