---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: indobert_sarcasm
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/arthad24/emotion_analysis_V2/runs/l0kjyqxw)
# indobert_sarcasm

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5596
- Accuracy: 0.7997
- F1: 0.7226
- Recall: 0.7148
- Precision: 0.7326

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.5348        | 1.0   | 385  | 0.4679          | 0.7815   | 0.5831 | 0.5821 | 0.7724    |
| 0.4424        | 2.0   | 770  | 0.4659          | 0.8016   | 0.6838 | 0.6619 | 0.7529    |
| 0.3403        | 3.0   | 1155 | 0.4683          | 0.8      | 0.7026 | 0.6851 | 0.7377    |
| 0.2386        | 4.0   | 1540 | 0.5596          | 0.7997   | 0.7226 | 0.7148 | 0.7326    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1