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  ---
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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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-
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- [More Information Needed]
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- ### Downstream Use [optional]
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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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- ## 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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- 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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- #### 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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- ### 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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- ## 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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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- ## Citation [optional]
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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 [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: cc-by-nc-4.0
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+ base_model: facebook/mms-1b-all
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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: mms-1b-all-lg-CV-v1
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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: lg
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+ split: None
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+ args: lg
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.24204557387377929
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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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+
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+ # mms-1b-all-lg-CV-v1
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+ This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) 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: inf
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+ - Wer: 0.2420
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+ - Cer: 0.0619
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+ More information needed
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+
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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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+
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 8
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+ - eval_batch_size: 4
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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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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+ | 0.2848 | 1.0 | 4442 | inf | 0.2783 | 0.0702 |
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+ | 0.1923 | 2.0 | 8884 | inf | 0.2848 | 0.0713 |
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+ | 0.1895 | 3.0 | 13326 | inf | 0.2710 | 0.0686 |
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+ | 0.1873 | 4.0 | 17768 | inf | 0.2712 | 0.0675 |
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+ | 0.1852 | 5.0 | 22210 | inf | 0.2710 | 0.0675 |
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+ | 0.1828 | 6.0 | 26652 | inf | 0.2696 | 0.0695 |
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+ | 0.1812 | 7.0 | 31094 | inf | 0.2756 | 0.0672 |
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+ | 0.1804 | 8.0 | 35536 | inf | 0.2717 | 0.0675 |
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+ | 0.1788 | 9.0 | 39978 | inf | 0.2592 | 0.0668 |
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+ | 0.1778 | 10.0 | 44420 | inf | 0.2590 | 0.0666 |
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+ | 0.1767 | 11.0 | 48862 | inf | 0.2619 | 0.0661 |
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+ | 0.1755 | 12.0 | 53304 | inf | 0.2580 | 0.0657 |
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+ | 0.1746 | 13.0 | 57746 | inf | 0.2545 | 0.0642 |
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+ | 0.1738 | 14.0 | 62188 | inf | 0.2579 | 0.0655 |
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+ | 0.1736 | 15.0 | 66630 | inf | 0.2565 | 0.0652 |
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+ | 0.1727 | 16.0 | 71072 | inf | 0.2572 | 0.0650 |
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+ | 0.172 | 17.0 | 75514 | inf | 0.2553 | 0.0644 |
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+ | 0.1717 | 18.0 | 79956 | inf | 0.2520 | 0.0636 |
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+ | 0.1706 | 19.0 | 84398 | inf | 0.2565 | 0.0645 |
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+ | 0.1697 | 20.0 | 88840 | inf | 0.2516 | 0.0637 |
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+ | 0.1696 | 21.0 | 93282 | inf | 0.2511 | 0.0632 |
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+ | 0.1686 | 22.0 | 97724 | inf | 0.2687 | 0.0657 |
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+ | 0.1688 | 23.0 | 102166 | inf | 0.2523 | 0.0639 |
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+ | 0.1673 | 24.0 | 106608 | inf | 0.2529 | 0.0644 |
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+ | 0.1671 | 25.0 | 111050 | inf | 0.2514 | 0.0637 |
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+ | 0.1664 | 26.0 | 115492 | inf | 0.2508 | 0.0636 |
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+ | 0.1666 | 27.0 | 119934 | inf | 0.2550 | 0.0637 |
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+ | 0.1655 | 28.0 | 124376 | inf | 0.2515 | 0.0636 |
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+ | 0.1649 | 29.0 | 128818 | inf | 0.2458 | 0.0628 |
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+ | 0.1647 | 30.0 | 133260 | inf | 0.2517 | 0.0637 |
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+ | 0.1641 | 31.0 | 137702 | inf | 0.2477 | 0.0628 |
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+ | 0.1637 | 32.0 | 142144 | inf | 0.2461 | 0.0629 |
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+ | 0.1629 | 33.0 | 146586 | inf | 0.2480 | 0.0635 |
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+ | 0.1628 | 34.0 | 151028 | inf | 0.2498 | 0.0633 |
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+ | 0.1625 | 35.0 | 155470 | inf | 0.2555 | 0.0638 |
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+ | 0.1619 | 36.0 | 159912 | inf | 0.2498 | 0.0639 |
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+ | 0.1625 | 37.0 | 164354 | inf | 0.2469 | 0.0628 |
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+ | 0.1613 | 38.0 | 168796 | inf | 0.2443 | 0.0630 |
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+ | 0.1618 | 39.0 | 173238 | inf | 0.2462 | 0.0635 |
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+ | 0.1611 | 40.0 | 177680 | inf | 0.2419 | 0.0622 |
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+ | 0.1604 | 41.0 | 182122 | inf | 0.2433 | 0.0627 |
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+ | 0.1592 | 42.0 | 186564 | inf | 0.2443 | 0.0628 |
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+ | 0.1598 | 43.0 | 191006 | inf | 0.2437 | 0.0629 |
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+ | 0.1589 | 44.0 | 195448 | inf | 0.2444 | 0.0627 |
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+ | 0.1589 | 45.0 | 199890 | inf | 0.2455 | 0.0628 |
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+ | 0.158 | 46.0 | 204332 | inf | 0.2384 | 0.0619 |
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+ | 0.1574 | 47.0 | 208774 | inf | 0.2455 | 0.0628 |
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+ | 0.157 | 48.0 | 213216 | inf | 0.2444 | 0.0620 |
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+ | 0.157 | 49.0 | 217658 | inf | 0.2428 | 0.0627 |
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+ | 0.1557 | 50.0 | 222100 | inf | 0.2423 | 0.0622 |
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+ | 0.1557 | 51.0 | 226542 | inf | 0.2420 | 0.0623 |
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+ | 0.1558 | 52.0 | 230984 | inf | 0.2483 | 0.0626 |
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+ | 0.1553 | 53.0 | 235426 | inf | 0.2406 | 0.0621 |
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+ | 0.155 | 54.0 | 239868 | inf | 0.2445 | 0.0608 |
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+ | 0.1545 | 55.0 | 244310 | inf | 0.2443 | 0.0617 |
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+ | 0.1546 | 56.0 | 248752 | inf | 0.2419 | 0.0614 |
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+ | 0.1537 | 57.0 | 253194 | inf | 0.2380 | 0.0612 |
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+ | 0.1532 | 58.0 | 257636 | inf | 0.2420 | 0.0619 |
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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