---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bertweetB_10epoch
  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_10epoch

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: 0.1462
- Accuracy: 0.7821
- Precision: 0.2467
- Recall: 0.3063
- F1: 0.2720

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 217  | 0.1311          | 0.8571   | 0.0       | 0.0    | 0.0    |
| No log        | 2.0   | 434  | 0.1296          | 0.8571   | 0.0       | 0.0    | 0.0    |
| 0.1928        | 3.0   | 651  | 0.1278          | 0.8571   | 0.0       | 0.0    | 0.0    |
| 0.1928        | 4.0   | 868  | 0.1248          | 0.8571   | 0.0       | 0.0    | 0.0    |
| 0.1547        | 5.0   | 1085 | 0.1353          | 0.8593   | 0.3747    | 0.0812 | 0.1334 |
| 0.1547        | 6.0   | 1302 | 0.1184          | 0.8464   | 0.3093    | 0.1550 | 0.2065 |
| 0.1191        | 7.0   | 1519 | 0.1224          | 0.8271   | 0.2845    | 0.2841 | 0.2834 |
| 0.1191        | 8.0   | 1736 | 0.1335          | 0.7936   | 0.2411    | 0.3358 | 0.2806 |
| 0.1191        | 9.0   | 1953 | 0.1376          | 0.8021   | 0.2630    | 0.2952 | 0.2765 |
| 0.0734        | 10.0  | 2170 | 0.1462          | 0.7821   | 0.2467    | 0.3063 | 0.2720 |


### Framework versions

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