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README.md
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library_name: transformers
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---
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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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#### 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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## 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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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: xlsr-aiish-nomiii
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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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# xlsr-aiish-nomiii
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0000
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- Wer: 0.3068
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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: 0.0004
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- train_batch_size: 8
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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: 16
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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: 132
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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 |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|
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| 4.6675 | 1.6327 | 200 | 2.6799 | 1.0 |
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| 1.8836 | 3.2653 | 400 | 0.3203 | 0.6161 |
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| 0.3406 | 4.8980 | 600 | 0.0509 | 0.4144 |
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| 0.1344 | 6.5306 | 800 | 0.0307 | 0.3704 |
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| 0.0919 | 8.1633 | 1000 | 0.0077 | 0.3093 |
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| 0.0576 | 9.7959 | 1200 | 0.0027 | 0.3105 |
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| 0.0488 | 11.4286 | 1400 | 0.0023 | 0.3093 |
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| 0.0497 | 13.0612 | 1600 | 0.0157 | 0.3178 |
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| 0.039 | 14.6939 | 1800 | 0.0007 | 0.3068 |
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| 0.0338 | 16.3265 | 2000 | 0.0086 | 0.3105 |
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| 0.0347 | 17.9592 | 2200 | 0.0020 | 0.3081 |
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| 0.0259 | 19.5918 | 2400 | 0.0004 | 0.3081 |
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| 0.0254 | 21.2245 | 2600 | 0.0268 | 0.3227 |
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| 0.0321 | 22.8571 | 2800 | 0.0093 | 0.3142 |
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| 0.0255 | 24.4898 | 3000 | 0.0003 | 0.3105 |
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| 0.0222 | 26.1224 | 3200 | 0.0004 | 0.3068 |
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| 0.0203 | 27.7551 | 3400 | 0.0106 | 0.3142 |
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| 0.0207 | 29.3878 | 3600 | 0.0005 | 0.3068 |
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| 0.0177 | 31.0204 | 3800 | 0.0012 | 0.3068 |
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| 0.0143 | 32.6531 | 4000 | 0.0002 | 0.3068 |
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| 0.0181 | 34.2857 | 4200 | 0.0003 | 0.3068 |
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| 0.0142 | 35.9184 | 4400 | 0.0002 | 0.3068 |
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| 0.0141 | 37.5510 | 4600 | 0.0003 | 0.3068 |
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| 0.0117 | 39.1837 | 4800 | 0.0001 | 0.3068 |
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| 0.0115 | 40.8163 | 5000 | 0.0001 | 0.3081 |
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| 0.0107 | 42.4490 | 5200 | 0.0002 | 0.3068 |
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| 0.0093 | 44.0816 | 5400 | 0.0001 | 0.3068 |
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| 0.0111 | 45.7143 | 5600 | 0.0004 | 0.3068 |
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| 0.013 | 47.3469 | 5800 | 0.0001 | 0.3068 |
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| 0.0115 | 48.9796 | 6000 | 0.0004 | 0.3068 |
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| 0.0109 | 50.6122 | 6200 | 0.0001 | 0.3068 |
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| 0.0073 | 52.2449 | 6400 | 0.0001 | 0.3068 |
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| 0.0058 | 53.8776 | 6600 | 0.0001 | 0.3068 |
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| 0.0123 | 55.5102 | 6800 | 0.0001 | 0.3068 |
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| 0.0119 | 57.1429 | 7000 | 0.0008 | 0.3081 |
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| 0.0108 | 58.7755 | 7200 | 0.0001 | 0.3068 |
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| 0.0069 | 60.4082 | 7400 | 0.0001 | 0.3068 |
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| 0.0054 | 62.0408 | 7600 | 0.0009 | 0.3081 |
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| 0.0066 | 63.6735 | 7800 | 0.0001 | 0.3068 |
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| 0.0072 | 65.3061 | 8000 | 0.0001 | 0.3068 |
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| 0.0049 | 66.9388 | 8200 | 0.0008 | 0.3068 |
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| 0.0054 | 68.5714 | 8400 | 0.0001 | 0.3068 |
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| 0.0048 | 70.2041 | 8600 | 0.0001 | 0.3068 |
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| 0.0046 | 71.8367 | 8800 | 0.0000 | 0.3068 |
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| 0.0034 | 73.4694 | 9000 | 0.0021 | 0.3093 |
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| 0.0049 | 75.1020 | 9200 | 0.0000 | 0.3068 |
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| 0.0016 | 76.7347 | 9400 | 0.0000 | 0.3068 |
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| 0.0039 | 78.3673 | 9600 | 0.0000 | 0.3068 |
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| 0.0036 | 80.0 | 9800 | 0.0000 | 0.3068 |
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| 0.0036 | 81.6327 | 10000 | 0.0000 | 0.3068 |
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| 0.0022 | 83.2653 | 10200 | 0.0006 | 0.3068 |
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| 0.0033 | 84.8980 | 10400 | 0.0000 | 0.3081 |
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| 0.0027 | 86.5306 | 10600 | 0.0000 | 0.3068 |
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| 0.0018 | 88.1633 | 10800 | 0.0000 | 0.3068 |
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| 0.0028 | 89.7959 | 11000 | 0.0000 | 0.3068 |
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| 0.0019 | 91.4286 | 11200 | 0.0000 | 0.3068 |
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| 0.0023 | 93.0612 | 11400 | 0.0000 | 0.3068 |
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| 0.0012 | 94.6939 | 11600 | 0.0000 | 0.3068 |
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| 0.0017 | 96.3265 | 11800 | 0.0000 | 0.3068 |
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| 0.0014 | 97.9592 | 12000 | 0.0000 | 0.3068 |
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| 0.0011 | 99.5918 | 12200 | 0.0000 | 0.3068 |
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### Framework versions
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- Transformers 4.46.0.dev0
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- Pytorch 2.4.0
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- Datasets 3.0.0
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- Tokenizers 0.20.0
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