---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch5
  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_3epoch5

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: 1.0827
- Accuracy: 0.7464
- F1: 0.4094
- Precision: 0.6162
- Recall: 0.3065
- Precision Sarcastic: 0.6162
- Recall Sarcastic: 0.3065
- F1 Sarcastic: 0.4094

## 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: 8
- eval_batch_size: 8
- 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     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 347  | 0.7068          | 0.7147   | 0.01   | 1.0       | 0.0050 | 1.0                 | 0.0050           | 0.01         |
| 0.52          | 2.0   | 694  | 0.5626          | 0.7478   | 0.4957 | 0.5811    | 0.4322 | 0.5811              | 0.4322           | 0.4957       |
| 0.3534        | 3.0   | 1041 | 0.8067          | 0.7651   | 0.4475 | 0.6875    | 0.3317 | 0.6875              | 0.3317           | 0.4475       |
| 0.3534        | 4.0   | 1388 | 0.9764          | 0.7378   | 0.4709 | 0.5586    | 0.4070 | 0.5586              | 0.4070           | 0.4709       |
| 0.1664        | 5.0   | 1735 | 1.0827          | 0.7464   | 0.4094 | 0.6162    | 0.3065 | 0.6162              | 0.3065           | 0.4094       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1