Edit model card

Wav2Vec2_xls_r_300m_hi_final

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the 'Openslr Multilingual and code-switching ASR challenge' dataset and 'mozilla-foundation/common_voice_7_0' dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3035
  • Wer: 0.3137
  • Cer: 0.0972

    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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 8
  • mixed_precision_training: Native AMP

    Training results

    Training Loss Epoch Step Validation Loss Wer Cer
    0.9821 0.64 400 0.5059 0.4783 0.1573
    0.6861 1.28 800 0.4201 0.4247 0.1356
    0.585 1.92 1200 0.3797 0.3811 0.1210
    0.5193 2.56 1600 0.3577 0.3652 0.1152
    0.4583 3.21 2000 0.3422 0.3519 0.1111
    0.4282 3.85 2400 0.3261 0.3450 0.1071
    0.3951 4.49 2800 0.3201 0.3325 0.1048
    0.3619 5.13 3200 0.3167 0.3296 0.1030
    0.345 5.77 3600 0.3157 0.3210 0.1013
    0.338 6.41 4000 0.3051 0.3143 0.0982
    0.3155 7.05 4400 0.3059 0.3154 0.0986
    0.3057 7.69 4800 0.3035 0.3137 0.0972

    Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.0
Downloads last month
5
Hosted inference API
or or
This model can be loaded on the Inference API on-demand.

Dataset used to train LegolasTheElf/Wav2Vec2_xls_r_lm_300m_hi

Evaluation results