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--- |
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language: |
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- sv |
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license: cc0-1.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_9_0 |
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- generated_from_trainer |
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- sv |
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datasets: |
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- mozilla-foundation/common_voice_9_0 |
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model-index: |
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- name: XLS-R-300M - Swedish |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_9_0 |
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type: mozilla-foundation/common_voice_9_0 |
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split: test |
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args: sv-SE |
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WER: |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 7.72 |
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- name: Test CER |
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type: cer |
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value: 2.61 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: speech-recognition-community-v2/dev_data |
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type: speech-recognition-community-v2/dev_data |
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split: validation |
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args: sv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 16.23 |
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- name: Test CER |
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type: cer |
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value: 8.21 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: speech-recognition-community-v2/dev_data |
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type: speech-recognition-community-v2/dev_data |
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split: test |
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args: sv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 15.08 |
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- name: Test CER |
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type: cer |
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value: 7.51 |
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--- |
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# |
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This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - SV-SE dataset. |
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It achieves the following results on the evaluation set ("test" split, without LM): |
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- Loss: 0.1318 |
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- Wer: 0.1121 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 7.5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.9099 | 10.42 | 1000 | 2.8369 | 1.0 | |
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| 1.0745 | 20.83 | 2000 | 0.1957 | 0.1673 | |
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| 0.934 | 31.25 | 3000 | 0.1579 | 0.1389 | |
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| 0.8691 | 41.66 | 4000 | 0.1457 | 0.1290 | |
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| 0.8328 | 52.08 | 5000 | 0.1435 | 0.1205 | |
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| 0.8068 | 62.5 | 6000 | 0.1350 | 0.1191 | |
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| 0.7822 | 72.91 | 7000 | 0.1347 | 0.1155 | |
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| 0.7769 | 83.33 | 8000 | 0.1321 | 0.1131 | |
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| 0.7678 | 93.75 | 9000 | 0.1321 | 0.1115 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 2.2.2 |
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- Tokenizers 0.11.0 |
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