---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bertweetB_15epoch
  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. -->

# bertweetB_15epoch

This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1645
- Accuracy: 0.77
- Precision: 0.2476
- Recall: 0.3173
- F1: 0.2757

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 217  | 0.1306          | 0.8571   | 0.0       | 0.0    | 0.0    |
| No log        | 2.0   | 434  | 0.1295          | 0.8571   | 0.0       | 0.0    | 0.0    |
| 0.1937        | 3.0   | 651  | 0.1268          | 0.8571   | 0.0       | 0.0    | 0.0    |
| 0.1937        | 4.0   | 868  | 0.1227          | 0.8593   | 0.3712    | 0.0701 | 0.1179 |
| 0.1473        | 5.0   | 1085 | 0.1307          | 0.765    | 0.2292    | 0.4354 | 0.3003 |
| 0.1473        | 6.0   | 1302 | 0.1270          | 0.7964   | 0.2457    | 0.3469 | 0.2877 |
| 0.1018        | 7.0   | 1519 | 0.1398          | 0.7607   | 0.2276    | 0.4354 | 0.2978 |
| 0.1018        | 8.0   | 1736 | 0.1449          | 0.7821   | 0.2323    | 0.3506 | 0.2786 |
| 0.1018        | 9.0   | 1953 | 0.1408          | 0.7843   | 0.2681    | 0.3764 | 0.3127 |
| 0.0648        | 10.0  | 2170 | 0.1535          | 0.78     | 0.2455    | 0.2878 | 0.2634 |
| 0.0648        | 11.0  | 2387 | 0.1585          | 0.7593   | 0.2375    | 0.3911 | 0.2954 |
| 0.0396        | 12.0  | 2604 | 0.1591          | 0.7757   | 0.2642    | 0.3100 | 0.2809 |
| 0.0396        | 13.0  | 2821 | 0.1670          | 0.7614   | 0.2347    | 0.3432 | 0.2774 |
| 0.0284        | 14.0  | 3038 | 0.1623          | 0.7793   | 0.2561    | 0.3026 | 0.2745 |
| 0.0284        | 15.0  | 3255 | 0.1645          | 0.77     | 0.2476    | 0.3173 | 0.2757 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1