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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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- ## 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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- 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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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: pic-20s_asr-scr_w2v2-base_003
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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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+ # pic-20s_asr-scr_w2v2-base_003
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4215
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+ - Per: 0.1497
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+ - Pcc: 0.6339
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+ - Ctc Loss: 0.5259
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+ - Mse Loss: 0.8821
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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: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 1
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+ - seed: 3333
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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: 2247
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+ - training_steps: 22470
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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 | Per | Pcc | Ctc Loss | Mse Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
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+ | 17.0464 | 3.0 | 2247 | 5.0097 | 0.9979 | 0.6184 | 3.7876 | 1.2860 |
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+ | 4.3019 | 6.0 | 4494 | 4.2229 | 0.9979 | 0.7055 | 3.7328 | 0.6675 |
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+ | 3.9383 | 9.0 | 6741 | 4.1717 | 0.9979 | 0.7012 | 3.7059 | 0.7331 |
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+ | 3.3316 | 12.0 | 8988 | 2.9515 | 0.6216 | 0.6761 | 2.3269 | 0.7956 |
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+ | 1.5694 | 15.0 | 11235 | 1.8634 | 0.2235 | 0.6674 | 0.8822 | 0.9706 |
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+ | 0.8929 | 18.0 | 13482 | 1.5733 | 0.1742 | 0.6392 | 0.6657 | 0.8867 |
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+ | 0.6847 | 21.0 | 15729 | 1.6522 | 0.1613 | 0.6497 | 0.5817 | 1.0250 |
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+ | 0.5739 | 24.0 | 17976 | 1.4394 | 0.1534 | 0.6165 | 0.5482 | 0.8750 |
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+ | 0.5063 | 27.0 | 20223 | 1.4105 | 0.1510 | 0.6296 | 0.5322 | 0.8668 |
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+ | 0.4701 | 30.0 | 22470 | 1.4215 | 0.1497 | 0.6339 | 0.5259 | 0.8821 |
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+ ### Framework versions
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+ - Transformers 4.38.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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