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README.md
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###
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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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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[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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#### Hardware
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#### Software
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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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## 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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## Model Card Contact
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[More Information Needed]
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---
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language:
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- tr
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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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- mozilla-foundation/common_voice_17
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model-index:
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- name: 'Wav2Vec2-XLS-TR '
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results: []
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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-XLS-TR
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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 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2925
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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: 0.0001
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- train_batch_size: 16
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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_ratio: 0.1
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- num_epochs: 30
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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 |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.6208 | 1.0 | 2901 | 0.3714 |
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| 0.4852 | 2.0 | 5802 | 0.3358 |
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| 0.4807 | 3.0 | 8703 | 0.4309 |
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| 0.441 | 4.0 | 11604 | 0.4345 |
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| 0.3965 | 5.0 | 14505 | 0.3815 |
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| 0.3429 | 6.0 | 17406 | 0.3601 |
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| 0.3074 | 7.0 | 20307 | 0.3551 |
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| 0.2913 | 8.0 | 23208 | 0.3477 |
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| 0.2744 | 9.0 | 26109 | 0.3262 |
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| 0.2611 | 10.0 | 29010 | 0.3225 |
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| 0.2359 | 11.0 | 31911 | 0.3244 |
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| 0.2398 | 12.0 | 34812 | 0.3053 |
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| 0.2085 | 13.0 | 37713 | 0.3058 |
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| 0.1903 | 14.0 | 40614 | 0.3219 |
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| 0.1827 | 15.0 | 43515 | 0.2911 |
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| 0.1654 | 16.0 | 46416 | 0.2890 |
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| 0.1548 | 17.0 | 49317 | 0.2945 |
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| 0.1467 | 18.0 | 52218 | 0.2807 |
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| 0.1399 | 19.0 | 55119 | 0.2914 |
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| 0.1272 | 20.0 | 58020 | 0.2974 |
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| 0.1162 | 21.0 | 60921 | 0.2991 |
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| 0.1056 | 22.0 | 63822 | 0.2743 |
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| 0.1004 | 23.0 | 66723 | 0.2932 |
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| 0.0926 | 24.0 | 69624 | 0.2806 |
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| 0.0855 | 25.0 | 72525 | 0.2872 |
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| 0.0802 | 26.0 | 75426 | 0.2732 |
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| 0.078 | 27.0 | 78327 | 0.2844 |
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| 0.0689 | 28.0 | 81228 | 0.2884 |
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| 0.0634 | 29.0 | 84129 | 0.2925 |
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| 0.0616 | 30.0 | 87030 | 0.2925 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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model.safetensors
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