without-cq / README.md
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without-cq
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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: without-cq
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. -->
# without-cq
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: 2.1785
- Accuracy: 0.6604
- Precision: 0.6734
- Recall: 0.6604
- F1: 0.6643
## 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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0888 | 1.0 | 266 | 1.9147 | 0.6660 | 0.6707 | 0.6660 | 0.6668 |
| 0.0379 | 2.0 | 532 | 2.1358 | 0.6566 | 0.6523 | 0.6566 | 0.6525 |
| 0.0568 | 3.0 | 798 | 2.1785 | 0.6604 | 0.6734 | 0.6604 | 0.6643 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1