Edit model card

wav2vec2-large-xls-r-300m-hsb-v2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HSB dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5328
  • Wer: 0.4596

Evaluation Commands

  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v2 --dataset mozilla-foundation/common_voice_8_0 --config hsb --split test --log_outputs

  1. To evaluate on speech-recognition-community-v2/dev_data

Upper Sorbian (hsb) not found in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00045
  • 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
8.5979 3.23 100 3.5602 1.0
3.303 6.45 200 3.2238 1.0
3.2034 9.68 300 3.2002 0.9888
2.7986 12.9 400 1.2408 0.9210
1.3869 16.13 500 0.7973 0.7462
1.0228 19.35 600 0.6722 0.6788
0.8311 22.58 700 0.6100 0.6150
0.717 25.81 800 0.6236 0.6013
0.6264 29.03 900 0.6031 0.5575
0.5494 32.26 1000 0.5656 0.5309
0.4781 35.48 1100 0.5289 0.4996
0.4311 38.71 1200 0.5375 0.4768
0.3902 41.94 1300 0.5246 0.4703
0.3508 45.16 1400 0.5382 0.4696
0.3199 48.39 1500 0.5328 0.4596

Framework versions

  • Transformers 4.16.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.2
  • Tokenizers 0.11.0
Downloads last month
15

Dataset used to train DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v2

Evaluation results