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---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-large-reddit-indonesia-sarcastic
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. -->
# xlm-roberta-large-reddit-indonesia-sarcastic
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co./xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4768
- Accuracy: 0.8120
- F1: 0.6274
- Precision: 0.6217
- Recall: 0.6331
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5177 | 1.0 | 309 | 0.4619 | 0.7867 | 0.4801 | 0.6150 | 0.3938 |
| 0.4158 | 2.0 | 618 | 0.4048 | 0.8143 | 0.5705 | 0.6770 | 0.4929 |
| 0.3535 | 3.0 | 927 | 0.4726 | 0.8051 | 0.4742 | 0.7294 | 0.3513 |
| 0.2983 | 4.0 | 1236 | 0.5060 | 0.8065 | 0.5806 | 0.6342 | 0.5354 |
| 0.2439 | 5.0 | 1545 | 0.4598 | 0.8143 | 0.6203 | 0.6350 | 0.6062 |
| 0.198 | 6.0 | 1854 | 0.5417 | 0.8058 | 0.5595 | 0.6468 | 0.4929 |
| 0.1655 | 7.0 | 2163 | 0.6252 | 0.8072 | 0.575 | 0.6411 | 0.5212 |
| 0.1242 | 8.0 | 2472 | 0.8431 | 0.8122 | 0.6051 | 0.6384 | 0.5751 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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