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wav2vec2-large-xls-r-300m-tatar

Automatic Speech Recognition
Transformers
PyTorch
Tatar
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results
Inference Endpoints
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metadata
language:
  - tt
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-tatar
    results: []

wav2vec2-large-xls-r-300m-tatar

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

  • Loss: 0.1959
  • Wer: 0.2454

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: 7e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 4000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.173 9.66 4000 0.2920 0.3608
0.9433 19.32 8000 0.2336 0.3026
0.8552 28.99 12000 0.2221 0.2799
0.7863 38.65 16000 0.1953 0.2479
0.7365 48.31 20000 0.1968 0.2449

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.0