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---
library_name: transformers
license: mit
base_model: w11wo/sundanese-roberta-base-emotion-classifier
tags:
- generated_from_trainer
model-index:
- name: RoBERTa-Base-Avg-SE2025T11A-sun-v20241224104615
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. -->
# RoBERTa-Base-Avg-SE2025T11A-sun-v20241224104615
This model is a fine-tuned version of [w11wo/sundanese-roberta-base-emotion-classifier](https://huggingface.co/w11wo/sundanese-roberta-base-emotion-classifier) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3618
- eval_model_preparation_time: 0.0032
- eval_f1_micro: 0.6933
- eval_f1_macro: 0.3543
- eval_f1_label_marah: 0.1538
- eval_f1_label_jijik: 0.2222
- eval_f1_label_takut: 0.0
- eval_f1_label_senang: 0.8763
- eval_f1_label_sedih: 0.6667
- eval_f1_label_terkejut: 0.3111
- eval_f1_label_biasa: 0.25
- eval_runtime: 1.8475
- eval_samples_per_second: 69.282
- eval_steps_per_second: 34.641
- step: 0
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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