outputs / README.md
hdc-labs's picture
update model card README.md
9228226
metadata
tags:
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: outputs
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice
          type: common_voice
          config: tr
          split: train+validation
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 0.35818608926565215

outputs

This model was trained from scratch on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3878
  • Wer: 0.3582

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: 64
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 1.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.7391 0.92 100 3.5760 1.0
2.927 1.83 200 3.0796 0.9999
0.9009 2.75 300 0.9278 0.8226
0.6529 3.67 400 0.5926 0.6367
0.3623 4.59 500 0.5372 0.5692
0.2888 5.5 600 0.4407 0.4838
0.285 6.42 700 0.4341 0.4694
0.0842 7.34 800 0.4153 0.4302
0.1415 8.26 900 0.4317 0.4136
0.1552 9.17 1000 0.4145 0.4013
0.1184 10.09 1100 0.4115 0.3844
0.0556 11.01 1200 0.4182 0.3862
0.0851 11.93 1300 0.3985 0.3688
0.0961 12.84 1400 0.4030 0.3665
0.0596 13.76 1500 0.3880 0.3631
0.0917 14.68 1600 0.3878 0.3582

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.6.1
  • Tokenizers 0.13.1