| --- |
| language: |
| - sv |
| license: cc0-1.0 |
| tags: |
| - automatic-speech-recognition |
| - mozilla-foundation/common_voice_9_0 |
| - generated_from_trainer |
| - sv |
| datasets: |
| - mozilla-foundation/common_voice_9_0 |
| model-index: |
| - name: XLS-R-300M - Swedish |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: mozilla-foundation/common_voice_9_0 |
| type: mozilla-foundation/common_voice_9_0 |
| split: test |
| args: sv-SE |
| WER: |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 7.72 |
| - name: Test CER |
| type: cer |
| value: 2.61 |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: speech-recognition-community-v2/dev_data |
| type: speech-recognition-community-v2/dev_data |
| split: validation |
| args: sv |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 16.23 |
| - name: Test CER |
| type: cer |
| value: 8.21 |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: speech-recognition-community-v2/dev_data |
| type: speech-recognition-community-v2/dev_data |
| split: test |
| args: sv |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 15.08 |
| - name: Test CER |
| type: cer |
| value: 7.51 |
| --- |
| # |
|
|
| 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. |
| It achieves the following results on the evaluation set ("test" split, without LM): |
| - Loss: 0.1318 |
| - Wer: 0.1121 |
| |
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.2 |
| - num_epochs: 100.0 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 2.9099 | 10.42 | 1000 | 2.8369 | 1.0 | |
| | 1.0745 | 20.83 | 2000 | 0.1957 | 0.1673 | |
| | 0.934 | 31.25 | 3000 | 0.1579 | 0.1389 | |
| | 0.8691 | 41.66 | 4000 | 0.1457 | 0.1290 | |
| | 0.8328 | 52.08 | 5000 | 0.1435 | 0.1205 | |
| | 0.8068 | 62.5 | 6000 | 0.1350 | 0.1191 | |
| | 0.7822 | 72.91 | 7000 | 0.1347 | 0.1155 | |
| | 0.7769 | 83.33 | 8000 | 0.1321 | 0.1131 | |
| | 0.7678 | 93.75 | 9000 | 0.1321 | 0.1115 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.17.0.dev0 |
| - Pytorch 1.10.2+cu102 |
| - Datasets 2.2.2 |
| - Tokenizers 0.11.0 |
| |
