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library_name: transformers
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Direct Use
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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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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<!-- 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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## Model Card Contact
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[More Information Needed]
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-xls-r-1b
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tags:
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- generated_from_trainer
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model-index:
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- name: wav2vec2-1b-Yfreq_pause
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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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# wav2vec2-1b-Yfreq_pause
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2859
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- Cer: 33.4880
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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: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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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: 50
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- num_epochs: 5
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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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| 12.7189 | 0.2580 | 200 | 4.6447 | 97.3156 |
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| 3.4682 | 0.5160 | 400 | 2.9509 | 67.6574 |
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| 1.7355 | 0.7741 | 600 | 2.5755 | 56.9666 |
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| 1.3168 | 1.0321 | 800 | 1.8127 | 48.0557 |
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| 1.0608 | 1.2901 | 1000 | 1.6916 | 45.5240 |
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| 0.9486 | 1.5481 | 1200 | 1.5227 | 41.0009 |
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| 0.8555 | 1.8062 | 1400 | 1.8282 | 48.3905 |
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| 0.7964 | 2.0642 | 1600 | 2.1936 | 54.9988 |
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| 0.6832 | 2.3222 | 1800 | 1.6408 | 40.3783 |
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| 0.5939 | 2.5802 | 2000 | 1.4571 | 39.3327 |
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| 0.5738 | 2.8383 | 2200 | 1.3655 | 37.2827 |
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| 0.4881 | 3.0963 | 2400 | 1.3322 | 34.9977 |
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| 0.4278 | 3.3543 | 2600 | 1.4489 | 36.8832 |
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| 0.3979 | 3.6123 | 2800 | 1.4433 | 37.5940 |
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| 0.36 | 3.8703 | 3000 | 1.3372 | 36.1490 |
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| 0.3348 | 4.1284 | 3200 | 1.3533 | 35.6203 |
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| 0.2949 | 4.3864 | 3400 | 1.3401 | 34.7568 |
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| 0.2703 | 4.6444 | 3600 | 1.3240 | 34.6746 |
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| 0.2519 | 4.9024 | 3800 | 1.2859 | 33.4880 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.3.1.post100
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- Datasets 2.19.1
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- Tokenizers 0.20.1
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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 3856393544
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version https://git-lfs.github.com/spec/v1
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oid sha256:13f3e7f4ab70f1fe795e8e4457108972604c7f0ce37f24014faca6ef397b770b
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size 3856393544
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