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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: '' |
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results: [] |
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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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# |
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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) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1355 |
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- Wer: 0.1531 |
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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: 64 |
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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: 2000 |
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- num_epochs: 3.0 |
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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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| 1.0826 | 0.07 | 1000 | 0.4637 | 0.4654 | |
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| 1.118 | 0.15 | 2000 | 0.2595 | 0.2687 | |
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| 1.1268 | 0.22 | 3000 | 0.2635 | 0.2661 | |
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| 1.0919 | 0.29 | 4000 | 0.2417 | 0.2566 | |
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| 1.1013 | 0.37 | 5000 | 0.2414 | 0.2567 | |
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| 1.0898 | 0.44 | 6000 | 0.2546 | 0.2731 | |
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| 1.0808 | 0.51 | 7000 | 0.2399 | 0.2535 | |
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| 1.0719 | 0.59 | 8000 | 0.2353 | 0.2528 | |
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| 1.0446 | 0.66 | 9000 | 0.2427 | 0.2545 | |
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| 1.0347 | 0.73 | 10000 | 0.2266 | 0.2402 | |
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| 1.0457 | 0.81 | 11000 | 0.2290 | 0.2448 | |
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| 1.0124 | 0.88 | 12000 | 0.2295 | 0.2448 | |
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| 1.025 | 0.95 | 13000 | 0.2138 | 0.2345 | |
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| 1.0107 | 1.03 | 14000 | 0.2108 | 0.2294 | |
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| 0.9758 | 1.1 | 15000 | 0.2019 | 0.2204 | |
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| 0.9547 | 1.17 | 16000 | 0.2000 | 0.2178 | |
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| 0.986 | 1.25 | 17000 | 0.2018 | 0.2200 | |
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| 0.9588 | 1.32 | 18000 | 0.1992 | 0.2138 | |
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| 0.9413 | 1.39 | 19000 | 0.1898 | 0.2049 | |
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| 0.9339 | 1.47 | 20000 | 0.1874 | 0.2056 | |
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| 0.9268 | 1.54 | 21000 | 0.1797 | 0.1976 | |
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| 0.9194 | 1.61 | 22000 | 0.1743 | 0.1905 | |
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| 0.8987 | 1.69 | 23000 | 0.1738 | 0.1932 | |
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| 0.8884 | 1.76 | 24000 | 0.1703 | 0.1873 | |
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| 0.8939 | 1.83 | 25000 | 0.1633 | 0.1831 | |
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| 0.8629 | 1.91 | 26000 | 0.1549 | 0.1750 | |
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| 0.8607 | 1.98 | 27000 | 0.1550 | 0.1738 | |
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| 0.8316 | 2.05 | 28000 | 0.1512 | 0.1709 | |
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| 0.8321 | 2.13 | 29000 | 0.1481 | 0.1657 | |
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| 0.825 | 2.2 | 30000 | 0.1446 | 0.1627 | |
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| 0.8115 | 2.27 | 31000 | 0.1396 | 0.1583 | |
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| 0.7959 | 2.35 | 32000 | 0.1389 | 0.1569 | |
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| 0.7835 | 2.42 | 33000 | 0.1362 | 0.1545 | |
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| 0.7959 | 2.49 | 34000 | 0.1355 | 0.1531 | |
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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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