| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: BERT_Offensive_English_Twitter |
| 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_Offensive_English_Twitter |
| |
| This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2731 |
| - Macro F1: 0.8890 |
| - Micro F1: 0.8954 |
| - Accuracy: 0.8954 |
| |
| ## 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: 8 |
| - eval_batch_size: 10 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Micro F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:| |
| | 0.3321 | 1.0 | 4036 | 0.6479 | 0.5302 | 0.5589 | 0.5589 | |
| | 0.4337 | 2.0 | 8073 | 0.3772 | 0.8346 | 0.8524 | 0.8524 | |
| | 0.2945 | 3.0 | 12109 | 0.3232 | 0.8753 | 0.8843 | 0.8843 | |
| | 0.243 | 4.0 | 16144 | 0.2731 | 0.8890 | 0.8954 | 0.8954 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.27.1 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.9.0 |
| - Tokenizers 0.13.3 |
|
|
