Hugging Face's logo

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

Automatic Speech Recognition
Transformers
PyTorch
Bulgarian
wav2vec2
Generated from Trainer
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results
Inference Endpoints
Model card Files Community
wav2vec2-large-xls-r-300m-bg-v1 / README.md
anton-l's picture
anton-l HF staff
Upload README.md
731afe4
preview code
|
raw
history blame contribute delete
4.03 kB
metadata
language:
  - bg
license: apache-2.0
tags:
  - automatic-speech-recognition
  - bg
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
datasets:
  - mozilla-foundation/common_voice_8_0
model-index:
  - name: wav2vec2-large-xls-r-300m-bg-v1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8
          type: mozilla-foundation/common_voice_8_0
          args: bg
        metrics:
          - name: Test WER
            type: wer
            value: 0.4709579127785184
          - name: Test CER
            type: cer
            value: 0.10205125354383235
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: bg
        metrics:
          - name: Test WER
            type: wer
            value: 0.7053128872366791
          - name: Test CER
            type: cer
            value: 0.210804311998487
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Test Data
          type: speech-recognition-community-v2/eval_data
          args: bg
        metrics:
          - name: Test WER
            type: wer
            value: 72.6

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