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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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- /workspace/data/uk/noizy_student_1/ |
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- generated_from_trainer |
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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 /WORKSPACE/DATA/UK/NOIZY_STUDENT_1/ - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1285 |
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- Wer: 0.1821 |
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- Cer: 0.0342 |
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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: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:| |
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| 1.2323 | 3.22 | 500 | 0.0797 | 0.2816 | 0.4133 | |
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| 0.9826 | 6.45 | 1000 | 0.0514 | 0.1970 | 0.2688 | |
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| 0.8628 | 9.67 | 1500 | 0.0474 | 0.1649 | 0.2485 | |
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| 0.8348 | 12.9 | 2000 | 0.0467 | 0.1605 | 0.2460 | |
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| 0.8186 | 16.13 | 2500 | 0.0469 | 0.1608 | 0.2469 | |
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| 0.8011 | 19.35 | 3000 | 0.1620 | 0.2412 | 0.0468 | |
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| 0.807 | 22.58 | 3500 | 0.1737 | 0.2524 | 0.0498 | |
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| 0.7758 | 25.8 | 4000 | 0.1709 | 0.2536 | 0.0498 | |
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| 0.7923 | 29.03 | 4500 | 0.1645 | 0.2436 | 0.0474 | |
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| 0.7717 | 32.26 | 5000 | 0.1811 | 0.2636 | 0.0524 | |
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| 0.7447 | 35.48 | 5500 | 0.1635 | 0.2405 | 0.0468 | |
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| 0.7267 | 38.71 | 6000 | 0.1578 | 0.2354 | 0.0462 | |
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| 0.7046 | 41.93 | 6500 | 0.1555 | 0.2296 | 0.0444 | |
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| 0.6896 | 45.16 | 7000 | 0.1548 | 0.2272 | 0.0439 | |
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| 0.6575 | 48.38 | 7500 | 0.1432 | 0.2096 | 0.0399 | |
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| 0.6264 | 51.61 | 8000 | 0.1466 | 0.2056 | 0.0398 | |
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| 0.589 | 54.83 | 8500 | 0.1351 | 0.1943 | 0.0371 | |
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| 0.573 | 58.06 | 9000 | 0.1387 | 0.1934 | 0.0365 | |
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| 0.5537 | 61.29 | 9500 | 0.1328 | 0.1883 | 0.0353 | |
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| 0.544 | 64.51 | 10000 | 0.1285 | 0.1821 | 0.0342 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2 |
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- Datasets 1.18.4.dev0 |
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- Tokenizers 0.11.0 |
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