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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_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: xls-r-300m-hbs-fr-unfrozen-batch16 |
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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_17_0 |
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type: common_voice_17_0 |
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config: hsb |
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split: test |
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args: hsb |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3959700093720712 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning/runs/pnc4tk8k) |
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# xls-r-300m-hbs-fr-unfrozen-batch16 |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7093 |
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- Wer: 0.3960 |
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- Cer: 0.0915 |
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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: 500 |
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- num_epochs: 100 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 3.5652 | 3.2258 | 100 | 3.3748 | 1.0 | 1.0 | |
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| 3.2583 | 6.4516 | 200 | 3.2149 | 1.0 | 1.0 | |
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| 3.1829 | 9.6774 | 300 | 3.1452 | 1.0 | 1.0 | |
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| 0.7256 | 12.9032 | 400 | 0.7889 | 0.7134 | 0.1766 | |
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| 0.3062 | 16.1290 | 500 | 0.6745 | 0.6146 | 0.1423 | |
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| 0.1843 | 19.3548 | 600 | 0.6301 | 0.5265 | 0.1242 | |
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| 0.1259 | 22.5806 | 700 | 0.6102 | 0.4820 | 0.1121 | |
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| 0.1386 | 25.8065 | 800 | 0.6702 | 0.4939 | 0.1176 | |
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| 0.0962 | 29.0323 | 900 | 0.6297 | 0.4806 | 0.1147 | |
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| 0.069 | 32.2581 | 1000 | 0.6766 | 0.4740 | 0.1113 | |
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| 0.0779 | 35.4839 | 1100 | 0.6565 | 0.4609 | 0.1075 | |
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| 0.0715 | 38.7097 | 1200 | 0.6649 | 0.4649 | 0.1103 | |
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| 0.0448 | 41.9355 | 1300 | 0.6558 | 0.4642 | 0.1094 | |
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| 0.0552 | 45.1613 | 1400 | 0.6893 | 0.4412 | 0.1035 | |
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| 0.0396 | 48.3871 | 1500 | 0.7179 | 0.4527 | 0.1041 | |
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| 0.0592 | 51.6129 | 1600 | 0.6455 | 0.4285 | 0.0976 | |
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| 0.0509 | 54.8387 | 1700 | 0.6605 | 0.4349 | 0.1005 | |
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| 0.0665 | 58.0645 | 1800 | 0.7340 | 0.4243 | 0.0991 | |
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| 0.0391 | 61.2903 | 1900 | 0.7378 | 0.4330 | 0.1018 | |
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| 0.0974 | 64.5161 | 2000 | 0.6984 | 0.4306 | 0.1003 | |
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| 0.0344 | 67.7419 | 2100 | 0.6895 | 0.4208 | 0.0974 | |
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| 0.043 | 70.9677 | 2200 | 0.7214 | 0.4140 | 0.0965 | |
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| 0.0248 | 74.1935 | 2300 | 0.7242 | 0.4149 | 0.0990 | |
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| 0.0194 | 77.4194 | 2400 | 0.7233 | 0.4107 | 0.0962 | |
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| 0.0277 | 80.6452 | 2500 | 0.7247 | 0.4100 | 0.0946 | |
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| 0.0447 | 83.8710 | 2600 | 0.7078 | 0.4004 | 0.0941 | |
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| 0.0291 | 87.0968 | 2700 | 0.7073 | 0.4002 | 0.0915 | |
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| 0.0208 | 90.3226 | 2800 | 0.7121 | 0.4025 | 0.0921 | |
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| 0.0278 | 93.5484 | 2900 | 0.6998 | 0.3932 | 0.0914 | |
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| 0.0569 | 96.7742 | 3000 | 0.7105 | 0.3964 | 0.0918 | |
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| 0.0132 | 100.0 | 3100 | 0.7093 | 0.3960 | 0.0915 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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