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End of training
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README.md
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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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<!-- 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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## 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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[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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model-index:
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- name: wav2vec2-Vocals-Kor
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results: []
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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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# wav2vec2-Vocals-Kor
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4436
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- Cer: 0.2135
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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_steps: 1000
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- num_epochs: 12
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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 | Cer |
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|:-------------:|:------:|:----:|:---------------:|:------:|
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| 10.0761 | 0.1181 | 300 | 3.5931 | 0.9861 |
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| 2.8824 | 0.2361 | 600 | 1.9956 | 0.6491 |
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| 1.1701 | 0.3542 | 900 | 0.8263 | 0.2735 |
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| 0.8015 | 0.4723 | 1200 | 0.6946 | 0.2530 |
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| 0.7235 | 0.5903 | 1500 | 0.6638 | 0.2380 |
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| 0.6747 | 0.7084 | 1800 | 0.6288 | 0.2399 |
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| 0.6528 | 0.8264 | 2100 | 0.5963 | 0.2382 |
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| 0.6185 | 0.9445 | 2400 | 0.6014 | 0.2412 |
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| 0.5861 | 1.0626 | 2700 | 0.5747 | 0.2388 |
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| 0.5668 | 1.1806 | 3000 | 0.5561 | 0.2199 |
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| 0.5628 | 1.2987 | 3300 | 0.5335 | 0.2235 |
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| 0.5521 | 1.4168 | 3600 | 0.5489 | 0.2290 |
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| 0.5309 | 1.5348 | 3900 | 0.4995 | 0.2125 |
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| 0.5033 | 1.6529 | 4200 | 0.4905 | 0.2171 |
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| 0.5018 | 1.7710 | 4500 | 0.4853 | 0.2129 |
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| 0.5011 | 1.8890 | 4800 | 0.4901 | 0.2171 |
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| 0.4907 | 2.0071 | 5100 | 0.4828 | 0.2135 |
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| 0.4578 | 2.1251 | 5400 | 0.4855 | 0.2180 |
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| 0.4552 | 2.2432 | 5700 | 0.4621 | 0.2216 |
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| 0.4345 | 2.3613 | 6000 | 0.4669 | 0.2152 |
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| 0.4332 | 2.4793 | 6300 | 0.4639 | 0.2171 |
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| 0.4338 | 2.5974 | 6600 | 0.4517 | 0.2180 |
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| 0.4181 | 2.7155 | 6900 | 0.4407 | 0.2117 |
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| 0.4048 | 2.8335 | 7200 | 0.4394 | 0.2063 |
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| 0.4003 | 2.9516 | 7500 | 0.4478 | 0.2100 |
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| 0.3847 | 3.0697 | 7800 | 0.4478 | 0.2159 |
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| 0.3634 | 3.1877 | 8100 | 0.4378 | 0.2145 |
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| 0.3629 | 3.3058 | 8400 | 0.4386 | 0.2060 |
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| 0.3603 | 3.4238 | 8700 | 0.4411 | 0.2127 |
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| 0.361 | 3.5419 | 9000 | 0.4436 | 0.2135 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.0
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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 1261991932
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version https://git-lfs.github.com/spec/v1
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oid sha256:26a384c0325d47b25c75bb9641011aa9bbf9f9d846d3432d661e655f1dcbaa6c
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size 1261991932
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