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training results in model card
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metadata
language:
  - or
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xls-r-300m-odia
    results: []

wav2vec2-large-xls-r-300m-odia

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - OR dataset. It achieves the following results on the evaluation set:

python eval.py --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config as --split test --log_outputs
  • WER: 0.7954545454545454
  • CER: 0.32341269841269843

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: 7.5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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: 120.0
  • mixed_precision_training: Native AMP

Training results

eval_loss eval_wer eval_runtime eval_samples_per_second eval_steps_per_second epoch
0 3.35224 0.998972 5.0475 22.189 1.387 29.41
1 1.33679 0.938335 5.0633 22.12 1.382 58.82
2 0.737202 0.957862 5.0913 21.998 1.375 88.24
3 0.658212 0.96814 5.0953 21.981 1.374 117.65
4 0.658 0.9712 5.0953 22.115 1.382 120

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0