adrianSauer's picture
End of training
78a69b0 verified
metadata
library_name: transformers
language:
  - gn
license: apache-2.0
base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Common Voice 16
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16
          type: mozilla-foundation/common_voice_16_1
          config: gn
          split: None
          args: gn
        metrics:
          - name: Wer
            type: wer
            value: 49.7001998667555

Common Voice 16

This model is a fine-tuned version of glob-asr/wav2vec2-large-xls-r-300m-guarani-small on the Common Voice 16 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4335
  • Wer: 49.7002

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: 8
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 3000
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.258 0.4955 500 0.3710 53.1646
0.921 0.9911 1000 0.3282 49.2338
0.7458 1.4866 1500 0.2940 46.7022
0.6763 1.9822 2000 0.2628 44.9700
0.568 2.4777 2500 0.2616 43.3711
0.5414 2.9732 3000 0.2504 39.8401
0.484 3.4688 3500 0.2462 41.0393
0.5281 3.9643 4000 0.3584 43.5043
0.5756 4.4599 4500 0.4220 44.3038
0.721 4.9554 5000 0.4335 49.7002

Framework versions

  • Transformers 4.44.1
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1