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--- |
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base_model: readerbench/RoBERT-base |
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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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- precision |
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- recall |
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model-index: |
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- name: ro-offense-01 |
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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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# ro-offense-01 |
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This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8411 |
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- Accuracy: 0.8232 |
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- Precision: 0.8235 |
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- Recall: 0.8210 |
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- F1 Macro: 0.8207 |
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- F1 Micro: 0.8232 |
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- F1 Weighted: 0.8210 |
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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: 4e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Macro | F1 Micro | F1 Weighted | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:-----------:| |
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| No log | 1.0 | 125 | 0.7789 | 0.7037 | 0.6825 | 0.7000 | 0.6873 | 0.7037 | 0.7132 | |
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| No log | 2.0 | 250 | 0.5170 | 0.8006 | 0.8066 | 0.8016 | 0.7986 | 0.8006 | 0.7971 | |
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| No log | 3.0 | 375 | 0.5139 | 0.8096 | 0.8168 | 0.8237 | 0.8120 | 0.8096 | 0.8047 | |
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| 0.6074 | 4.0 | 500 | 0.6180 | 0.8247 | 0.8251 | 0.8187 | 0.8210 | 0.8247 | 0.8233 | |
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| 0.6074 | 5.0 | 625 | 0.7311 | 0.8096 | 0.8071 | 0.8085 | 0.8064 | 0.8096 | 0.8071 | |
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| 0.6074 | 6.0 | 750 | 0.8365 | 0.8101 | 0.8117 | 0.8191 | 0.8105 | 0.8101 | 0.8051 | |
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| 0.6074 | 7.0 | 875 | 0.8411 | 0.8232 | 0.8235 | 0.8210 | 0.8207 | 0.8232 | 0.8210 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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