End of training
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README.md
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---
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base_model: klue/roberta-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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model-index:
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- name: roberta-base-finetuned-hate_speech
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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-base-finetuned-hate_speech
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This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8142
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- F1: 0.6357
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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: 2e-05
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- train_batch_size: 128
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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_steps: 10
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 1.0 | 44 | 0.8284 | 0.5900 |
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| No log | 2.0 | 88 | 0.7911 | 0.6091 |
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| No log | 3.0 | 132 | 0.7954 | 0.6231 |
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| No log | 4.0 | 176 | 0.8142 | 0.6357 |
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| No log | 5.0 | 220 | 0.8523 | 0.6227 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.17.0
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- Tokenizers 0.15.2
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model.safetensors
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