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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bertweet-base_finetuned_olid_c
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. -->
# bertweet-base_finetuned_olid_c
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7880
- Accuracy: 0.7324
- F1-macro: 0.6299
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.9373 | 1.0 | 61 | 0.8441 | 0.6948 | 0.5042 |
| 0.7817 | 2.0 | 122 | 0.8038 | 0.7230 | 0.5247 |
| 0.7258 | 3.0 | 183 | 0.7837 | 0.7324 | 0.5772 |
| 0.6596 | 4.0 | 244 | 0.7812 | 0.7371 | 0.6255 |
| 0.6247 | 5.0 | 305 | 0.7880 | 0.7324 | 0.6299 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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