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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: xlsr-128upper-sorbian |
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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: validation |
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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: 0.5044303797468355 |
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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-new/runs/0wnfr6i1) |
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# xlsr-128upper-sorbian |
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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: 0.7625 |
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- Wer: 0.5044 |
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- Cer: 0.1106 |
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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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| 3.8489 | 3.9216 | 100 | 4.0479 | 1.0 | 1.0 | |
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| 3.1996 | 7.8431 | 200 | 3.2124 | 0.9804 | 0.9850 | |
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| 2.3527 | 11.7647 | 300 | 2.4026 | 1.0 | 0.6858 | |
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| 0.4424 | 15.6863 | 400 | 0.7917 | 0.7418 | 0.1910 | |
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| 0.2617 | 19.6078 | 500 | 0.7624 | 0.6804 | 0.1696 | |
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| 0.1421 | 23.5294 | 600 | 0.7839 | 0.6582 | 0.1579 | |
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| 0.097 | 27.4510 | 700 | 0.8322 | 0.6316 | 0.1495 | |
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| 0.0459 | 31.3725 | 800 | 0.8119 | 0.6171 | 0.1446 | |
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| 0.0668 | 35.2941 | 900 | 0.8534 | 0.6418 | 0.1535 | |
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| 0.0627 | 39.2157 | 1000 | 0.8256 | 0.6019 | 0.1397 | |
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| 0.0454 | 43.1373 | 1100 | 0.7747 | 0.5994 | 0.1363 | |
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| 0.04 | 47.0588 | 1200 | 0.8046 | 0.5810 | 0.1321 | |
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| 0.0563 | 50.9804 | 1300 | 0.7910 | 0.5797 | 0.1325 | |
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| 0.039 | 54.9020 | 1400 | 0.7370 | 0.5595 | 0.1265 | |
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| 0.0254 | 58.8235 | 1500 | 0.7395 | 0.5418 | 0.1188 | |
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| 0.0211 | 62.7451 | 1600 | 0.7582 | 0.5430 | 0.1209 | |
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| 0.0218 | 66.6667 | 1700 | 0.7123 | 0.5051 | 0.1121 | |
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| 0.0206 | 70.5882 | 1800 | 0.7912 | 0.5297 | 0.1165 | |
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| 0.0155 | 74.5098 | 1900 | 0.7671 | 0.5367 | 0.1183 | |
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| 0.0242 | 78.4314 | 2000 | 0.7926 | 0.5418 | 0.1170 | |
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| 0.0081 | 82.3529 | 2100 | 0.7817 | 0.5373 | 0.1221 | |
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| 0.0087 | 86.2745 | 2200 | 0.7989 | 0.5285 | 0.1165 | |
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| 0.0088 | 90.1961 | 2300 | 0.7523 | 0.5165 | 0.1141 | |
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| 0.0173 | 94.1176 | 2400 | 0.7646 | 0.5038 | 0.1108 | |
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| 0.0217 | 98.0392 | 2500 | 0.7625 | 0.5044 | 0.1106 | |
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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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