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YAML Metadata
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"language[0]" with value "sv-SE" is not valid. It must be an ISO 639-1, 639-2 or 639-3 code (two/three letters), or a special value like "code", "multilingual". If you want to use BCP-47 identifiers, you can specify them in language_bcp47.
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset. It achieves the following results on the evaluation set:
- Loss: 0.2604
- Wer: 0.2334
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 1
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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
See Tensorboard
Evaluation Commands
- To evaluate on
mozilla-foundation/common_voice_7_0
with splittest
python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset mozilla-foundation/common_voice_7_0 --config sv-SE --split test
- To evaluate on
speech-recognition-community-v2/dev_data
python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.18.4.dev0
- Tokenizers 0.10.3
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Dataset used to train patrickvonplaten/xls-r-300-sv-cv7
Evaluation results
- Test WER on Common Voice 7self-reported15.990
- Test CER on Common Voice 7self-reported5.200
- Test WER on Robust Speech Event - Dev Dataself-reported24.410
- Test CER on Robust Speech Event - Dev Dataself-reported11.880