results / README.md
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: results
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: ne-NP
          split: validated+other
          args: ne-NP
        metrics:
          - name: Wer
            type: wer
            value: 0.5865921787709497

results

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7289
  • Wer: 0.5866

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: 0.0003
  • 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: 200
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4919 2.9851 100 1.2236 0.9106
1.0086 5.9701 200 0.9436 0.8291
0.6072 8.9552 300 0.8277 0.7117
0.55 11.9403 400 0.7774 0.6726
0.3398 14.9254 500 0.7344 0.6212
0.2543 17.9104 600 0.7368 0.6212
0.3558 20.8955 700 0.7313 0.5788
0.1751 23.8806 800 0.7060 0.5855
0.1502 26.8657 900 0.7289 0.5866

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1