---
base_model: xxxxxxxxx
tags:
- generated_from_trainer
datasets:
- AmazonScience/massive
metrics:
- f1
model-index:
- name: massive_indo
  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. -->

# massive_indo

This model is a fine-tuned version of [xxxxxxxxx](https://huggingface.co/xxxxxxxxx) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6572
- F1: 0.9265

## 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
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.6759        | 0.7   | 100  | 4.5686          | 0.0756 |
| 4.1696        | 1.41  | 200  | 4.1337          | 0.1459 |
| 3.7162        | 2.11  | 300  | 3.7519          | 0.2513 |
| 3.3933        | 2.82  | 400  | 3.4123          | 0.3291 |
| 3.0368        | 3.52  | 500  | 3.0874          | 0.4287 |
| 2.7163        | 4.23  | 600  | 2.7851          | 0.5446 |
| 2.4295        | 4.93  | 700  | 2.5342          | 0.5967 |
| 2.192         | 5.63  | 800  | 2.2814          | 0.6738 |
| 1.9818        | 6.34  | 900  | 2.0643          | 0.7221 |
| 1.7487        | 7.04  | 1000 | 1.8860          | 0.7589 |
| 1.6227        | 7.75  | 1100 | 1.7132          | 0.8021 |
| 1.4186        | 8.45  | 1200 | 1.5550          | 0.8249 |
| 1.2316        | 9.15  | 1300 | 1.4266          | 0.8378 |
| 1.1508        | 9.86  | 1400 | 1.3024          | 0.8547 |
| 1.0137        | 10.56 | 1500 | 1.1962          | 0.8708 |
| 0.9242        | 11.27 | 1600 | 1.1050          | 0.8807 |
| 0.877         | 11.97 | 1700 | 1.0273          | 0.8908 |
| 0.7244        | 12.68 | 1800 | 0.9580          | 0.8946 |
| 0.7141        | 13.38 | 1900 | 0.8928          | 0.9016 |
| 0.6071        | 14.08 | 2000 | 0.8448          | 0.9128 |
| 0.6166        | 14.79 | 2100 | 0.7980          | 0.9112 |
| 0.6017        | 15.49 | 2200 | 0.7613          | 0.9175 |
| 0.5192        | 16.2  | 2300 | 0.7300          | 0.9204 |
| 0.4669        | 16.9  | 2400 | 0.7112          | 0.9172 |
| 0.4539        | 17.61 | 2500 | 0.6872          | 0.9247 |
| 0.438         | 18.31 | 2600 | 0.6698          | 0.9248 |
| 0.4435        | 19.01 | 2700 | 0.6612          | 0.9256 |
| 0.4141        | 19.72 | 2800 | 0.6572          | 0.9265 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3