reichenbach's picture
Update README.md
b6c73f2
|
raw
history blame
2.09 kB
metadata
license: apache-2.0
language:
  - hi
tags:
  - generated_from_trainer
  - robust-speech-event
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xls-r-300m-hi
    results: []

wav2vec2-large-xls-r-300m-hi

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

  • Loss: 2.4749
  • Wer: 0.9420

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: 8
  • 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: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
9.8626 4.76 400 3.6151 1.0
3.5463 9.52 800 3.5778 1.0
3.4415 14.28 1200 3.4525 1.0
3.0927 19.05 1600 2.6220 0.9860
2.0573 23.8 2000 2.3974 0.9610
1.5905 28.57 2400 2.4427 0.9558
1.426 33.33 2800 2.4736 0.9475
1.3147 38.09 3200 2.4494 0.9417
1.2642 42.85 3600 2.4665 0.9450
1.2289 47.62 4000 2.4749 0.9420

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.10.3