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MinhND2301
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toxic_classification_model

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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MinhND2301 commited on
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End of training

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  1. README.md +15 -18
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
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- base_model: vinai/phobert-base
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  tags:
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  - generated_from_trainer
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  metrics:
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- - f1
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- - precision
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- - recall
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  model-index:
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- - name: my_model
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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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- # model_without_stopwords
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- This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3275
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- - F1: 0.7678
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- - Precision: 0.7851
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- - Recall: 0.7512
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  ## Model description
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@@ -41,19 +37,20 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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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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- - num_epochs: 2
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
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- | 0.1919 | 1.0 | 2423 | 0.3585 | 0.7545 | 0.7644 | 0.7448 |
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- | 0.2079 | 2.0 | 4846 | 0.3275 | 0.7678 | 0.7851 | 0.7512 |
 
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  ### Framework versions
 
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  ---
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+ base_model: MinhND2301/toxic_classification_model
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  tags:
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  - generated_from_trainer
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  metrics:
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+ - accuracy
 
 
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  model-index:
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+ - name: toxic_classification_model
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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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+ # toxic_classification_model
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+ This model is a fine-tuned version of [MinhND2301/toxic_classification_model](https://huggingface.co/MinhND2301/toxic_classification_model) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3017
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+ - Accuracy: 0.9108
 
 
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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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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+ - num_epochs: 3
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 436 | 0.2677 | 0.9009 |
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+ | 0.1858 | 2.0 | 872 | 0.2940 | 0.9030 |
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+ | 0.151 | 3.0 | 1308 | 0.3017 | 0.9108 |
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  ### Framework versions
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