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---
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
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