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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- multilingual_librispeech |
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- generated_from_trainer |
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datasets: |
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- multilingual_librispeech |
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model-index: |
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- name: wav2vec2-300m-mls-german-ft |
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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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# wav2vec2-300m-mls-german-ft |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MULTILINGUAL_LIBRISPEECH - GERMAN 10h dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2398 |
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- Wer: 0.1520 |
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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: 0.0001 |
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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: 1000 |
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- num_epochs: 200.0 |
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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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| 3.0132 | 7.25 | 500 | 2.9393 | 1.0 | |
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| 2.9241 | 14.49 | 1000 | 2.8734 | 1.0 | |
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| 1.0766 | 21.74 | 1500 | 0.2773 | 0.2488 | |
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| 0.8416 | 28.99 | 2000 | 0.2224 | 0.1990 | |
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| 0.8048 | 36.23 | 2500 | 0.2063 | 0.1792 | |
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| 0.7664 | 43.48 | 3000 | 0.2088 | 0.1748 | |
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| 0.6571 | 50.72 | 3500 | 0.2042 | 0.1668 | |
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| 0.7014 | 57.97 | 4000 | 0.2136 | 0.1649 | |
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| 0.6171 | 65.22 | 4500 | 0.2139 | 0.1641 | |
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| 0.6609 | 72.46 | 5000 | 0.2144 | 0.1621 | |
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| 0.6318 | 79.71 | 5500 | 0.2129 | 0.1600 | |
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| 0.6222 | 86.96 | 6000 | 0.2124 | 0.1582 | |
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| 0.608 | 94.2 | 6500 | 0.2255 | 0.1639 | |
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| 0.6099 | 101.45 | 7000 | 0.2265 | 0.1622 | |
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| 0.6069 | 108.7 | 7500 | 0.2246 | 0.1593 | |
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| 0.5929 | 115.94 | 8000 | 0.2323 | 0.1617 | |
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| 0.6218 | 123.19 | 8500 | 0.2287 | 0.1566 | |
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| 0.5751 | 130.43 | 9000 | 0.2275 | 0.1563 | |
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| 0.5181 | 137.68 | 9500 | 0.2316 | 0.1579 | |
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| 0.6306 | 144.93 | 10000 | 0.2372 | 0.1556 | |
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| 0.5874 | 152.17 | 10500 | 0.2362 | 0.1533 | |
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| 0.5546 | 159.42 | 11000 | 0.2342 | 0.1543 | |
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| 0.6294 | 166.67 | 11500 | 0.2381 | 0.1536 | |
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| 0.5989 | 173.91 | 12000 | 0.2360 | 0.1527 | |
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| 0.5697 | 181.16 | 12500 | 0.2399 | 0.1526 | |
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| 0.5379 | 188.41 | 13000 | 0.2375 | 0.1523 | |
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| 0.5022 | 195.65 | 13500 | 0.2395 | 0.1519 | |
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### Framework versions |
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- Transformers 4.13.0.dev0 |
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- Pytorch 1.10.0 |
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- Datasets 1.15.2.dev0 |
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- Tokenizers 0.10.3 |
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