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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-300m-colab-only-gn |
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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: 0.5229303156640858 |
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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-300m-colab-only-gn |
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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: 0.5274 |
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- Wer: 0.5229 |
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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: 30 |
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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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| 20.8148 | 0.45 | 25 | 13.5976 | 1.0 | |
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| 7.0188 | 0.9 | 50 | 5.5263 | 1.0 | |
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| 4.1285 | 1.35 | 75 | 3.6078 | 1.0 | |
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| 3.338 | 1.8 | 100 | 3.3217 | 1.0 | |
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| 3.2829 | 2.25 | 125 | 3.2781 | 1.0 | |
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| 3.272 | 2.7 | 150 | 3.2601 | 1.0 | |
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| 3.2224 | 3.15 | 175 | 3.2234 | 1.0 | |
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| 3.1949 | 3.6 | 200 | 3.1998 | 1.0 | |
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| 3.1846 | 4.05 | 225 | 3.1841 | 1.0 | |
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| 3.1615 | 4.5 | 250 | 3.1719 | 1.0 | |
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| 3.1367 | 4.95 | 275 | 3.1132 | 1.0 | |
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| 3.0111 | 5.41 | 300 | 2.9344 | 1.0 | |
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| 2.7786 | 5.86 | 325 | 2.5643 | 1.0 | |
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| 2.2106 | 6.31 | 350 | 1.8132 | 1.0 | |
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| 1.6365 | 6.76 | 375 | 1.4008 | 0.9982 | |
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| 1.178 | 7.21 | 400 | 1.0678 | 0.9845 | |
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| 0.8903 | 7.66 | 425 | 0.8744 | 0.9369 | |
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| 0.7429 | 8.11 | 450 | 0.7213 | 0.8752 | |
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| 0.5931 | 8.56 | 475 | 0.6681 | 0.8189 | |
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| 0.5592 | 9.01 | 500 | 0.6622 | 0.7895 | |
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| 0.4316 | 9.46 | 525 | 0.6177 | 0.7644 | |
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| 0.4098 | 9.91 | 550 | 0.5599 | 0.7874 | |
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| 0.3176 | 10.36 | 575 | 0.5649 | 0.7001 | |
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| 0.3142 | 10.81 | 600 | 0.5828 | 0.6867 | |
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| 0.3227 | 11.26 | 625 | 0.5505 | 0.6736 | |
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| 0.275 | 11.71 | 650 | 0.5432 | 0.6540 | |
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| 0.2783 | 12.16 | 675 | 0.5372 | 0.6462 | |
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| 0.2316 | 12.61 | 700 | 0.5078 | 0.6379 | |
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| 0.2281 | 13.06 | 725 | 0.5059 | 0.6161 | |
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| 0.2191 | 13.51 | 750 | 0.5175 | 0.5956 | |
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| 0.1911 | 13.96 | 775 | 0.5216 | 0.5929 | |
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| 0.1731 | 14.41 | 800 | 0.5069 | 0.5789 | |
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| 0.1743 | 14.86 | 825 | 0.5207 | 0.5971 | |
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| 0.1755 | 15.32 | 850 | 0.5436 | 0.6307 | |
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| 0.1568 | 15.77 | 875 | 0.5374 | 0.6001 | |
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| 0.1629 | 16.22 | 900 | 0.5429 | 0.6102 | |
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| 0.1418 | 16.67 | 925 | 0.5089 | 0.5762 | |
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| 0.136 | 17.12 | 950 | 0.5291 | 0.5878 | |
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| 0.1354 | 17.57 | 975 | 0.5381 | 0.5840 | |
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| 0.1351 | 18.02 | 1000 | 0.5511 | 0.5947 | |
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| 0.1252 | 18.47 | 1025 | 0.5204 | 0.5643 | |
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| 0.1215 | 18.92 | 1050 | 0.5385 | 0.5613 | |
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| 0.1188 | 19.37 | 1075 | 0.5063 | 0.5718 | |
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| 0.1209 | 19.82 | 1100 | 0.5211 | 0.5488 | |
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| 0.1091 | 20.27 | 1125 | 0.5245 | 0.5557 | |
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| 0.112 | 20.72 | 1150 | 0.4910 | 0.5587 | |
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| 0.102 | 21.17 | 1175 | 0.5192 | 0.5581 | |
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| 0.0947 | 21.62 | 1200 | 0.5500 | 0.5718 | |
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| 0.1066 | 22.07 | 1225 | 0.5288 | 0.5488 | |
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| 0.1011 | 22.52 | 1250 | 0.5180 | 0.5438 | |
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| 0.0974 | 22.97 | 1275 | 0.5089 | 0.5277 | |
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| 0.0926 | 23.42 | 1300 | 0.5222 | 0.5301 | |
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| 0.0871 | 23.87 | 1325 | 0.5135 | 0.5366 | |
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| 0.0808 | 24.32 | 1350 | 0.4990 | 0.5331 | |
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| 0.0739 | 24.77 | 1375 | 0.5281 | 0.5351 | |
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| 0.0841 | 25.23 | 1400 | 0.5321 | 0.5360 | |
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| 0.0743 | 25.68 | 1425 | 0.5508 | 0.5447 | |
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| 0.0809 | 26.13 | 1450 | 0.5228 | 0.5396 | |
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| 0.0631 | 26.58 | 1475 | 0.5284 | 0.5351 | |
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| 0.0788 | 27.03 | 1500 | 0.5250 | 0.5289 | |
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| 0.0754 | 27.48 | 1525 | 0.5204 | 0.5259 | |
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| 0.0663 | 27.93 | 1550 | 0.5275 | 0.5313 | |
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| 0.0645 | 28.38 | 1575 | 0.5288 | 0.5259 | |
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| 0.0729 | 28.83 | 1600 | 0.5268 | 0.5259 | |
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| 0.0656 | 29.28 | 1625 | 0.5277 | 0.5232 | |
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| 0.0703 | 29.73 | 1650 | 0.5274 | 0.5229 | |
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### Framework versions |
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- Transformers 4.34.1 |
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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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