model1_test / README.md
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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: model1_test
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. -->
# model1_test
This model is a fine-tuned version of [DaNLP/da-bert-hatespeech-detection](https://huggingface.co/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