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DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.052 GBother✓ 2 checksumsupdated today
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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BG dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5197
  • Wer: 0.4689

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-bg-v1 --dataset mozilla-foundation/common_voice_8_0 --config bg --split test --log_outputs

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

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1 --dataset speech-recognition-community-v2/dev_data --config bg --split validation --chunk_length_s 10 --stride_length_s 1

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: 2000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.3711 2.61 300 4.3122 1.0
3.1653 5.22 600 3.1156 1.0
2.8904 7.83 900 2.8421 0.9918
0.9207 10.43 1200 0.9895 0.8689
0.6384 13.04 1500 0.6994 0.7700
0.5215 15.65 1800 0.5628 0.6443
0.4573 18.26 2100 0.5316 0.6174
0.3875 20.87 2400 0.4932 0.5779
0.3562 23.48 2700 0.4972 0.5475
0.3218 26.09 3000 0.4895 0.5219
0.2954 28.7 3300 0.5226 0.5192
0.287 31.3 3600 0.4957 0.5146
0.2587 33.91 3900 0.4944 0.4893
0.2496 36.52 4200 0.4976 0.4895
0.2365 39.13 4500 0.5185 0.4819
0.2264 41.74 4800 0.5152 0.4776
0.2224 44.35 5100 0.5031 0.4746
0.2096 46.96 5400 0.5062 0.4708
0.2038 49.57 5700 0.5217 0.4698

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0