---
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: 0.1219
- F1: 0.9750

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.1726        | 0.58  | 100  | 2.2176          | 0.6600 |
| 1.7054        | 1.16  | 200  | 1.0444          | 0.8521 |
| 0.7568        | 1.73  | 300  | 0.4974          | 0.9248 |
| 0.3368        | 2.31  | 400  | 0.2992          | 0.9454 |
| 0.165         | 2.89  | 500  | 0.2052          | 0.9606 |
| 0.0739        | 3.47  | 600  | 0.1621          | 0.9665 |
| 0.0438        | 4.05  | 700  | 0.1568          | 0.9656 |
| 0.0228        | 4.62  | 800  | 0.1331          | 0.9711 |
| 0.0183        | 5.2   | 900  | 0.1249          | 0.9734 |
| 0.011         | 5.78  | 1000 | 0.1238          | 0.9733 |
| 0.0091        | 6.36  | 1100 | 0.1221          | 0.9741 |
| 0.0079        | 6.94  | 1200 | 0.1207          | 0.9756 |
| 0.007         | 7.51  | 1300 | 0.1218          | 0.9750 |
| 0.0064        | 8.09  | 1400 | 0.1216          | 0.9745 |
| 0.006         | 8.67  | 1500 | 0.1218          | 0.9749 |
| 0.0058        | 9.25  | 1600 | 0.1217          | 0.9750 |
| 0.0056        | 9.83  | 1700 | 0.1219          | 0.9750 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.14.1