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---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased-Hate_Offensive_or_Normal_Speech
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-large-uncased-Hate_Offensive_or_Normal_Speech
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0610
- Accuracy: 0.9853
- Weighted f1: 0.9853
- Weighted recall: 0.9853
- Weighted precision: 0.9854
- Micro f1: 0.9853
- Micro recall: 0.9853
- Micro precision: 0.9853
- Macro f1: 0.9851
- Macro recall: 0.9850
- Macro precision: 0.9853
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Weighted recall | Weighted precision | Micro f1 | Micro recall | Micro precision | Macro f1 | Macro recall | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| 0.2927 | 1.0 | 153 | 0.1163 | 0.9462 | 0.9469 | 0.9462 | 0.9512 | 0.9462 | 0.9462 | 0.9462 | 0.9429 | 0.9472 | 0.9427 |
| 0.066 | 2.0 | 306 | 0.1119 | 0.9739 | 0.9739 | 0.9739 | 0.9741 | 0.9739 | 0.9739 | 0.9739 | 0.9729 | 0.9742 | 0.9718 |
| 0.0267 | 3.0 | 459 | 0.0805 | 0.9821 | 0.9821 | 0.9821 | 0.9825 | 0.9821 | 0.9821 | 0.9821 | 0.9804 | 0.9815 | 0.9796 |
| 0.0209 | 4.0 | 612 | 0.0610 | 0.9853 | 0.9853 | 0.9853 | 0.9854 | 0.9853 | 0.9853 | 0.9853 | 0.9851 | 0.9850 | 0.9853 |
| 0.0097 | 5.0 | 765 | 0.0673 | 0.9837 | 0.9836 | 0.9837 | 0.9838 | 0.9837 | 0.9837 | 0.9837 | 0.9832 | 0.9833 | 0.9833 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3
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