metadata

language:
  - lg
license: apache-2.0
tags:
  - automatic-speech-recognition
  - robust-speech-event
  - common_voice
  - lg
  - generated_from_trainer
  - hf-asr-leaderboard
datasets:
  - common_voice
model-index:
  - name: wav2vec2-xls-r-300m-lg
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: sv-SE
        metrics:
          - name: Test WER
            type: wer
            value: 78.89
          - name: Test CER
            type: cer
            value: 15.16

wav2vec2-xls-r-300m-lg

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

Loss: 0.6989
Wer: 0.8529

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.9089	6.33	500	2.8983	1.0002
2.5754	12.66	1000	1.8710	1.0
1.4093	18.99	1500	0.7195	0.8547

Framework versions

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

Evaluation Commands

To evaluate on mozilla-foundation/common_voice_7_0 with split test

python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-lg --dataset mozilla-foundation/common_voice_7_0 --config lg --split test