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###
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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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-300-cv17-polish-adap-cs
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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: pl
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split: validation
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args: pl
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metrics:
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- name: Wer
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type: wer
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value: 0.3181674482322567
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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-polish/runs/gugvjjo9)
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# xls-r-300-cv17-polish-adap-cs
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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: 0.4585
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- Wer: 0.3182
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- Cer: 0.0713
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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: 50
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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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| 3.5986 | 1.6 | 100 | 3.9654 | 0.9986 | 0.9660 |
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| 3.2886 | 3.2 | 200 | 3.4889 | 1.0 | 1.0 |
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| 3.1683 | 4.8 | 300 | 3.1937 | 0.9946 | 0.9735 |
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| 2.7362 | 6.4 | 400 | 2.6853 | 1.0 | 0.8424 |
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| 0.6269 | 8.0 | 500 | 0.5183 | 0.5745 | 0.1381 |
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| 0.2661 | 9.6 | 600 | 0.4218 | 0.4551 | 0.1048 |
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| 0.1646 | 11.2 | 700 | 0.4160 | 0.4211 | 0.0985 |
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| 0.1197 | 12.8 | 800 | 0.4793 | 0.4578 | 0.1072 |
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| 0.1925 | 14.4 | 900 | 0.4402 | 0.4283 | 0.0969 |
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| 0.1132 | 16.0 | 1000 | 0.4253 | 0.3909 | 0.0906 |
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| 0.0851 | 17.6 | 1100 | 0.4609 | 0.3951 | 0.0921 |
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| 0.0799 | 19.2 | 1200 | 0.4453 | 0.3944 | 0.0907 |
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| 0.0657 | 20.8 | 1300 | 0.4681 | 0.3846 | 0.0887 |
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| 0.1188 | 22.4 | 1400 | 0.4575 | 0.3785 | 0.0873 |
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| 0.1088 | 24.0 | 1500 | 0.4649 | 0.3824 | 0.0882 |
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| 0.0698 | 25.6 | 1600 | 0.4496 | 0.3611 | 0.0817 |
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| 0.0575 | 27.2 | 1700 | 0.4459 | 0.3585 | 0.0822 |
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| 0.0705 | 28.8 | 1800 | 0.4542 | 0.3608 | 0.0820 |
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| 0.0524 | 30.4 | 1900 | 0.4785 | 0.3549 | 0.0814 |
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| 0.0338 | 32.0 | 2000 | 0.4566 | 0.3521 | 0.0801 |
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| 0.0357 | 33.6 | 2100 | 0.4597 | 0.3472 | 0.0783 |
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| 0.0477 | 35.2 | 2200 | 0.4626 | 0.3451 | 0.0788 |
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| 0.0478 | 36.8 | 2300 | 0.4730 | 0.3375 | 0.0765 |
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| 0.0568 | 38.4 | 2400 | 0.4713 | 0.3333 | 0.0749 |
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| 0.0217 | 40.0 | 2500 | 0.4701 | 0.3324 | 0.0755 |
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| 0.0404 | 41.6 | 2600 | 0.4585 | 0.3278 | 0.0740 |
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| 0.0118 | 43.2 | 2700 | 0.4656 | 0.3259 | 0.0736 |
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| 0.0374 | 44.8 | 2800 | 0.4625 | 0.3249 | 0.0731 |
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| 0.0417 | 46.4 | 2900 | 0.4599 | 0.3206 | 0.0721 |
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| 0.0378 | 48.0 | 3000 | 0.4614 | 0.3195 | 0.0717 |
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| 0.0381 | 49.6 | 3100 | 0.4585 | 0.3182 | 0.0713 |
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1262000180
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version https://git-lfs.github.com/spec/v1
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oid sha256:d2c2dbc6c373c360b63cc53cd72227653031be5b1f3ddb748dbb6f2fd2ea8abe
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size 1262000180
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