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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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- 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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- <!-- 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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- ### 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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- ## Training Details
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- #### Preprocessing [optional]
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- [More Information Needed]
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- ## Evaluation
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+ license: mit
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+ base_model: facebook/w2v-bert-2.0
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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: pashto-asr-v3
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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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+ # pashto-asr-v3
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+ This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1448
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+ - Wer: 0.1396
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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: 5e-05
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+ - train_batch_size: 4
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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: 32
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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: 500
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+ - training_steps: 1300
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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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+ | 2.9698 | 0.8089 | 100 | 2.8928 | 0.9991 |
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+ | 0.8095 | 1.6178 | 200 | 0.6035 | 0.4036 |
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+ | 0.6152 | 2.4267 | 300 | 0.4857 | 0.3593 |
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+ | 0.3951 | 3.2356 | 400 | 0.4661 | 0.3505 |
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+ | 0.5493 | 4.0445 | 500 | 0.3651 | 0.2779 |
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+ | 0.4588 | 4.8534 | 600 | 0.3244 | 0.2632 |
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+ | 0.3616 | 5.6623 | 700 | 0.2954 | 0.2490 |
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+ | 0.1938 | 6.4712 | 800 | 0.2655 | 0.2341 |
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+ | 0.2047 | 7.2801 | 900 | 0.2510 | 0.2022 |
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+ | 0.2596 | 8.0890 | 1000 | 0.1953 | 0.1756 |
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+ | 0.1871 | 8.8979 | 1100 | 0.1716 | 0.1642 |
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+ | 0.0768 | 9.7068 | 1200 | 0.1559 | 0.1554 |
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+ | 0.1021 | 10.5157 | 1300 | 0.1448 | 0.1396 |
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+ ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1