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---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
model-index:
- name: bertweet-base
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
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: 0.5822
- F1 Macro: 0.7750
- F1: 0.8571
- F1 Neg: 0.6929
- Acc: 0.805
- Prec: 0.8069
- Recall: 0.9141
- Mcc: 0.5646
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
| 0.6482 | 1.0 | 600 | 0.5610 | 0.6822 | 0.8022 | 0.5622 | 0.7275 | 0.7492 | 0.8633 | 0.3812 |
| 0.5567 | 2.0 | 1200 | 0.5125 | 0.7382 | 0.8364 | 0.64 | 0.775 | 0.7823 | 0.8984 | 0.4938 |
| 0.4549 | 3.0 | 1800 | 0.6164 | 0.7195 | 0.7588 | 0.6802 | 0.725 | 0.865 | 0.6758 | 0.4688 |
| 0.4021 | 4.0 | 2400 | 0.5785 | 0.7344 | 0.7875 | 0.6812 | 0.745 | 0.8438 | 0.7383 | 0.4789 |
| 0.3159 | 5.0 | 3000 | 0.5822 | 0.7750 | 0.8571 | 0.6929 | 0.805 | 0.8069 | 0.9141 | 0.5646 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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