| --- |
| language: |
| - as |
| license: apache-2.0 |
| tags: |
| - automatic-speech-recognition |
| - mozilla-foundation/common_voice_8_0 |
| - generated_from_trainer |
| - as |
| - robust-speech-event |
| - model_for_talk |
| - hf-asr-leaderboard |
| datasets: |
| - common_voice |
| model-index: |
| - name: wav2vec2-large-xls-r-300m-as-with-LM-v2 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 8 |
| type: mozilla-foundation/common_voice_8_0 |
| args: hsb |
| metrics: |
| - name: Test WER |
| type: wer |
| value: [] |
| - name: Test CER |
| type: cer |
| value: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
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|
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|
|
| ### Note: Files are missing. Probably, didn't get (git)pushed properly. :( |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1679 |
| - Wer: 0.5761 |
| |
| ## 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: 0.000111 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 300 |
| - num_epochs: 200 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 8.3852 | 10.51 | 200 | 3.6402 | 1.0 | |
| | 3.5374 | 21.05 | 400 | 3.3894 | 1.0 | |
| | 2.8645 | 31.56 | 600 | 1.3143 | 0.8303 | |
| | 1.1784 | 42.1 | 800 | 0.9417 | 0.6661 | |
| | 0.7805 | 52.62 | 1000 | 0.9292 | 0.6237 | |
| | 0.5973 | 63.15 | 1200 | 0.9489 | 0.6014 | |
| | 0.4784 | 73.67 | 1400 | 0.9916 | 0.5962 | |
| | 0.4138 | 84.21 | 1600 | 1.0272 | 0.6121 | |
| | 0.3491 | 94.72 | 1800 | 1.0412 | 0.5984 | |
| | 0.3062 | 105.26 | 2000 | 1.0769 | 0.6005 | |
| | 0.2707 | 115.77 | 2200 | 1.0708 | 0.5752 | |
| | 0.2459 | 126.31 | 2400 | 1.1285 | 0.6009 | |
| | 0.2234 | 136.82 | 2600 | 1.1209 | 0.5949 | |
| | 0.2035 | 147.36 | 2800 | 1.1348 | 0.5842 | |
| | 0.1876 | 157.87 | 3000 | 1.1480 | 0.5872 | |
| | 0.1669 | 168.41 | 3200 | 1.1496 | 0.5838 | |
| | 0.1595 | 178.92 | 3400 | 1.1721 | 0.5778 | |
| | 0.1505 | 189.46 | 3600 | 1.1654 | 0.5744 | |
| | 0.1486 | 199.97 | 3800 | 1.1679 | 0.5761 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.16.1 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.18.2 |
| - Tokenizers 0.11.0 |
| |
