| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - tweet_eval |
| metrics: |
| - f1 |
| model-index: |
| - name: hate_trained |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: tweet_eval |
| type: tweet_eval |
| args: hate |
| metrics: |
| - name: F1 |
| type: f1 |
| value: 0.7875737774565976 |
| --- |
| |
| <!-- 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. --> |
|
|
| # hate_trained |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8182 |
| - F1: 0.7876 |
|
|
| ## 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: 2.7272339744854407e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 0 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.4635 | 1.0 | 563 | 0.4997 | 0.7530 | |
| | 0.3287 | 2.0 | 1126 | 0.5138 | 0.7880 | |
| | 0.216 | 3.0 | 1689 | 0.6598 | 0.7821 | |
| | 0.1309 | 4.0 | 2252 | 0.8182 | 0.7876 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.13.0 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.16.1 |
| - Tokenizers 0.10.3 |
|
|
