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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-gn-pt |
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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_13_0 |
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type: common_voice_13_0 |
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config: gn |
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split: test |
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args: gn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5431804645622395 |
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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-large-xls-r-300m-gn-pt |
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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 common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6822 |
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- Wer: 0.5432 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 100 |
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- num_epochs: 35 |
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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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| 4.1972 | 0.79 | 400 | 1.9288 | 1.0045 | |
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| 0.9928 | 1.58 | 800 | 0.8247 | 0.9452 | |
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| 0.6075 | 2.36 | 1200 | 0.7675 | 0.8451 | |
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| 0.4724 | 3.15 | 1600 | 0.5485 | 0.7111 | |
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| 0.3879 | 3.94 | 2000 | 0.5885 | 0.7433 | |
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| 0.3152 | 4.73 | 2400 | 0.7606 | 0.7695 | |
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| 0.2872 | 5.52 | 2800 | 0.5723 | 0.6608 | |
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| 0.258 | 6.31 | 3200 | 0.5971 | 0.6820 | |
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| 0.2317 | 7.09 | 3600 | 0.5845 | 0.6471 | |
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| 0.2137 | 7.88 | 4000 | 0.7690 | 0.7198 | |
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| 0.193 | 8.67 | 4400 | 0.6219 | 0.6614 | |
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| 0.1795 | 9.46 | 4800 | 0.6203 | 0.6703 | |
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| 0.1768 | 10.25 | 5200 | 0.5645 | 0.6164 | |
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| 0.1637 | 11.03 | 5600 | 0.5804 | 0.6412 | |
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| 0.1573 | 11.82 | 6000 | 0.5914 | 0.5896 | |
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| 0.1467 | 12.61 | 6400 | 0.6517 | 0.6200 | |
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| 0.141 | 13.4 | 6800 | 0.6376 | 0.6310 | |
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| 0.135 | 14.19 | 7200 | 0.6343 | 0.6042 | |
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| 0.1279 | 14.98 | 7600 | 0.6680 | 0.6325 | |
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| 0.1222 | 15.76 | 8000 | 0.7109 | 0.6617 | |
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| 0.1169 | 16.55 | 8400 | 0.7067 | 0.6361 | |
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| 0.114 | 17.34 | 8800 | 0.7143 | 0.6144 | |
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| 0.1085 | 18.13 | 9200 | 0.6871 | 0.6081 | |
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| 0.0996 | 18.92 | 9600 | 0.8332 | 0.6569 | |
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| 0.0952 | 19.7 | 10000 | 0.7076 | 0.5992 | |
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| 0.0929 | 20.49 | 10400 | 0.6946 | 0.6078 | |
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| 0.0871 | 21.28 | 10800 | 0.6197 | 0.5822 | |
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| 0.0823 | 22.07 | 11200 | 0.6969 | 0.5876 | |
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| 0.0776 | 22.86 | 11600 | 0.6285 | 0.5619 | |
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| 0.0758 | 23.65 | 12000 | 0.7098 | 0.6010 | |
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| 0.0728 | 24.43 | 12400 | 0.6618 | 0.5905 | |
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| 0.0664 | 25.22 | 12800 | 0.6484 | 0.5536 | |
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| 0.0656 | 26.01 | 13200 | 0.6417 | 0.5593 | |
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| 0.0603 | 26.8 | 13600 | 0.7287 | 0.5813 | |
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| 0.0571 | 27.59 | 14000 | 0.6727 | 0.5700 | |
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| 0.0559 | 28.37 | 14400 | 0.6775 | 0.5631 | |
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| 0.0555 | 29.16 | 14800 | 0.7849 | 0.5968 | |
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| 0.0506 | 29.95 | 15200 | 0.8266 | 0.6185 | |
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| 0.0485 | 30.74 | 15600 | 0.7347 | 0.5747 | |
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| 0.0461 | 31.53 | 16000 | 0.6836 | 0.5432 | |
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| 0.0423 | 32.32 | 16400 | 0.6913 | 0.5396 | |
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| 0.0407 | 33.1 | 16800 | 0.6655 | 0.5328 | |
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| 0.04 | 33.89 | 17200 | 0.6873 | 0.5399 | |
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| 0.0396 | 34.68 | 17600 | 0.6822 | 0.5432 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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