metadata
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: model1_test
results: []
model1_test
This model is a fine-tuned version of DaNLP/da-bert-hatespeech-detection on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2219
- Accuracy: 0.9625
- F1: 0.2105
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 150 | 0.1116 | 0.9700 | 0.1818 |
| No log | 2.0 | 300 | 0.1649 | 0.9609 | 0.2295 |
| No log | 3.0 | 450 | 0.2219 | 0.9625 | 0.2105 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3