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README.md
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---
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license: apache-2.0
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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: distilbert-base-uncased__hate_speech_offensive__train-32-1
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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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# distilbert-base-uncased__hate_speech_offensive__train-32-1
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0606
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- Accuracy: 0.4745
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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: 4
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- eval_batch_size: 4
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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: 50
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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 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.0941 | 1.0 | 19 | 1.1045 | 0.2 |
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| 0.9967 | 2.0 | 38 | 1.1164 | 0.35 |
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| 0.8164 | 3.0 | 57 | 1.1570 | 0.4 |
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| 0.5884 | 4.0 | 76 | 1.2403 | 0.35 |
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| 0.3322 | 5.0 | 95 | 1.3815 | 0.35 |
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| 0.156 | 6.0 | 114 | 1.8102 | 0.3 |
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| 0.0576 | 7.0 | 133 | 2.1439 | 0.4 |
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| 0.0227 | 8.0 | 152 | 2.4368 | 0.3 |
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| 0.0133 | 9.0 | 171 | 2.5994 | 0.4 |
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| 0.009 | 10.0 | 190 | 2.7388 | 0.35 |
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| 0.0072 | 11.0 | 209 | 2.8287 | 0.35 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2
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- Tokenizers 0.10.3
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