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--- |
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language: |
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- cs |
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- hsb |
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- pl |
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- sk |
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- sl |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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- xlsr-fine-tuning-week |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-xls-r-300m-west-slavic-cv8 |
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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 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: cs |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 53.5 |
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- name: Test CER |
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type: cer |
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value: 14.7 |
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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 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: hsb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 81.7 |
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- name: Test CER |
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type: cer |
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value: 21.2 |
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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 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: pl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 60.2 |
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- name: Test CER |
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type: cer |
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value: 15.6 |
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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 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: sk |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 69.6 |
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- name: Test CER |
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type: cer |
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value: 20.7 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
|
dataset: |
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name: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 73.2 |
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- name: Test CER |
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type: cer |
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value: 23.2 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: cs |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 84.11 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: cs |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 75.99 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: pl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 65.3 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: pl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 72.0 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: sk |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 88.37 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: sk |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 89.08 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 87.69 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 87.89 |
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--- |
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# wav2vec2-xls-r-300m-west-slavic-cv8 |
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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 8 dataset of five similar languages with similar scripts: Czech, Slovak, Polish, Slovenian and Upper Sorbian. Training and validation sets were concatenated and shuffled. |
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Evaluation set used for training was concatenated from the respective test sets and shuffled while limiting each language to at most 2000 samples. During training, cca WER 70 was achieved on this set. |
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### Evaluation script |
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``` |
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python eval.py --model_id comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 --dataset mozilla-foundation/common_voice_8_0 --split test --config {lang} |
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``` |
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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: 32 |
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- eval_batch_size: 16 |
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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: 500 |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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