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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- fi |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: wav2vec2-xlsr-1b-fi |
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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: Common Voice 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: fi |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 13.11 |
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- name: Test CER |
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type: cer |
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value: 2.23 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-xlsr-1b-fi |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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_steps: 500 |
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- num_epochs: 5 |
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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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| 0.968 | 0.18 | 500 | 0.4870 | 0.4720 | |
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| 0.6557 | 0.36 | 1000 | 0.2450 | 0.2931 | |
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| 0.647 | 0.54 | 1500 | 0.1818 | 0.2255 | |
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| 0.5297 | 0.72 | 2000 | 0.1698 | 0.2354 | |
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| 0.5802 | 0.9 | 2500 | 0.1581 | 0.2355 | |
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| 0.6351 | 1.07 | 3000 | 0.1689 | 0.2336 | |
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| 0.4626 | 1.25 | 3500 | 0.1719 | 0.3099 | |
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| 0.4526 | 1.43 | 4000 | 0.1434 | 0.2069 | |
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| 0.4692 | 1.61 | 4500 | 0.1645 | 0.2192 | |
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| 0.4584 | 1.79 | 5000 | 0.1483 | 0.1987 | |
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| 0.4234 | 1.97 | 5500 | 0.1499 | 0.2178 | |
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| 0.4243 | 2.15 | 6000 | 0.1345 | 0.2070 | |
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| 0.4108 | 2.33 | 6500 | 0.1383 | 0.1850 | |
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| 0.4048 | 2.51 | 7000 | 0.1338 | 0.1811 | |
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| 0.4085 | 2.69 | 7500 | 0.1290 | 0.1780 | |
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| 0.4026 | 2.87 | 8000 | 0.1239 | 0.1650 | |
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| 0.4033 | 3.04 | 8500 | 0.1346 | 0.1657 | |
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| 0.3986 | 3.22 | 9000 | 0.1310 | 0.1850 | |
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| 0.3867 | 3.4 | 9500 | 0.1273 | 0.1741 | |
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| 0.3658 | 3.58 | 10000 | 0.1219 | 0.1672 | |
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| 0.382 | 3.76 | 10500 | 0.1306 | 0.1698 | |
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| 0.3847 | 3.94 | 11000 | 0.1230 | 0.1577 | |
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| 0.3691 | 4.12 | 11500 | 0.1310 | 0.1615 | |
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| 0.3593 | 4.3 | 12000 | 0.1296 | 0.1622 | |
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| 0.3619 | 4.48 | 12500 | 0.1285 | 0.1601 | |
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| 0.3361 | 4.66 | 13000 | 0.1261 | 0.1569 | |
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| 0.3603 | 4.84 | 13500 | 0.1235 | 0.1533 | |
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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 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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