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---
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license: apache-2.0
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base_model: distilroberta-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: RoBERTa_Self_Trained
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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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# RoBERTa_Self_Trained
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4069
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- Precision: 0.6923
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- Recall: 0.6923
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- F1: 0.6923
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- Accuracy: 0.8958
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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: 8
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- eval_batch_size: 8
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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 | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 10 | 0.7092 | 0.0 | 0.0 | 0.0 | 0.7458 |
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| No log | 2.0 | 20 | 0.4925 | 0.1 | 0.0769 | 0.0870 | 0.7917 |
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| No log | 3.0 | 30 | 0.4069 | 0.6923 | 0.6923 | 0.6923 | 0.8958 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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