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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: 0.7965
- F1 Macro: 0.8142
- F1: 0.8639
- F1 Neg: 0.7645
- Acc: 0.8275
- Prec: 0.8725
- Recall: 0.8555
- Mcc: 0.6287
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
| 0.6396 | 1.0 | 614 | 0.6126 | 0.7238 | 0.7652 | 0.6824 | 0.73 | 0.8627 | 0.6875 | 0.4734 |
| 0.4753 | 2.0 | 1228 | 0.5095 | 0.8057 | 0.8669 | 0.7445 | 0.825 | 0.8444 | 0.8906 | 0.6138 |
| 0.3965 | 3.0 | 1842 | 0.7932 | 0.7358 | 0.8527 | 0.6188 | 0.7875 | 0.7664 | 0.9609 | 0.5306 |
| 0.3534 | 4.0 | 2456 | 0.8950 | 0.7831 | 0.8140 | 0.7522 | 0.7875 | 0.9254 | 0.7266 | 0.5975 |
| 0.2284 | 5.0 | 3070 | 0.7965 | 0.8142 | 0.8639 | 0.7645 | 0.8275 | 0.8725 | 0.8555 | 0.6287 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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