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: 0.1816
- Accuracy: 0.9667
- F1: 0.3548
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 | 0.1128 | 0.9667 | 0.2 |
No log | 2.0 | 300 | 0.1666 | 0.9684 | 0.2963 |
No log | 3.0 | 450 | 0.1816 | 0.9667 | 0.3548 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
- Downloads last month
- 10
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.