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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
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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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- ### Model Description
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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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- ## Uses
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- ### Direct Use
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- ### Downstream Use [optional]
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- ## Bias, Risks, and 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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- ### 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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- ## Evaluation
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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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- ## Technical Specifications [optional]
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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-nm-clp
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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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+ # xlsr-nm-clp
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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: 1.3632
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+ - Wer: 0.5241
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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: 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: 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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+ | 5.0552 | 4.8780 | 200 | 3.0646 | 1.0 |
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+ | 3.0248 | 9.7561 | 400 | 2.9305 | 1.0 |
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+ | 2.8381 | 14.6341 | 600 | 2.7349 | 1.0 |
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+ | 2.2963 | 19.5122 | 800 | 1.9857 | 0.9550 |
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+ | 1.3557 | 24.3902 | 1000 | 1.3196 | 0.7685 |
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+ | 0.6411 | 29.2683 | 1200 | 1.3063 | 0.6881 |
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+ | 0.394 | 34.1463 | 1400 | 1.2477 | 0.6527 |
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+ | 0.2608 | 39.0244 | 1600 | 1.1584 | 0.6013 |
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+ | 0.1804 | 43.9024 | 1800 | 1.2374 | 0.6013 |
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+ | 0.1442 | 48.7805 | 2000 | 1.3478 | 0.5643 |
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+ | 0.1264 | 53.6585 | 2200 | 1.2854 | 0.5740 |
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+ | 0.0892 | 58.5366 | 2400 | 1.2293 | 0.5900 |
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+ | 0.0813 | 63.4146 | 2600 | 1.2025 | 0.5482 |
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+ | 0.0597 | 68.2927 | 2800 | 1.3339 | 0.5466 |
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+ | 0.0495 | 73.1707 | 3000 | 1.4527 | 0.5595 |
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+ | 0.0453 | 78.0488 | 3200 | 1.4188 | 0.5257 |
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+ | 0.0402 | 82.9268 | 3400 | 1.2740 | 0.5289 |
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+ | 0.0367 | 87.8049 | 3600 | 1.3237 | 0.5161 |
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+ | 0.0324 | 92.6829 | 3800 | 1.3321 | 0.5177 |
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+ | 0.0267 | 97.5610 | 4000 | 1.3632 | 0.5241 |
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+ ### Framework versions
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+ - Transformers 4.47.0.dev0
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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