digidaw1 / README.md
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---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: digidaw1
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. -->
# digidaw1
This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6456
- Accuracy: 0.8144
- Precision: 0.6187
- Recall: 0.5638
- F1: 0.5781
## 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: 0.0001
- 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
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9527 | 1.0 | 110 | 0.6411 | 0.7884 | 0.5621 | 0.5346 | 0.5342 |
| 0.5329 | 2.0 | 220 | 0.6017 | 0.8084 | 0.5649 | 0.5733 | 0.5642 |
| 0.2822 | 3.0 | 330 | 0.6456 | 0.8144 | 0.6187 | 0.5638 | 0.5781 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1