---
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: 0.4772
- F1: 0.9465

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5227        | 0.7   | 100  | 4.4260          | 0.0998 |
| 3.9734        | 1.41  | 200  | 3.9864          | 0.2616 |
| 3.6121        | 2.11  | 300  | 3.5977          | 0.3561 |
| 3.2481        | 2.82  | 400  | 3.2366          | 0.4929 |
| 2.9212        | 3.52  | 500  | 2.9196          | 0.5677 |
| 2.5236        | 4.23  | 600  | 2.6016          | 0.6625 |
| 2.3089        | 4.93  | 700  | 2.3252          | 0.7196 |
| 2.0311        | 5.63  | 800  | 2.0840          | 0.7740 |
| 1.793         | 6.34  | 900  | 1.8612          | 0.8168 |
| 1.5913        | 7.04  | 1000 | 1.6588          | 0.8524 |
| 1.4071        | 7.75  | 1100 | 1.4833          | 0.8781 |
| 1.2169        | 8.45  | 1200 | 1.3214          | 0.8806 |
| 1.1085        | 9.15  | 1300 | 1.2012          | 0.8983 |
| 0.9752        | 9.86  | 1400 | 1.0659          | 0.9145 |
| 0.8891        | 10.56 | 1500 | 0.9672          | 0.9165 |
| 0.7205        | 11.27 | 1600 | 0.8726          | 0.9225 |
| 0.6869        | 11.97 | 1700 | 0.8065          | 0.9320 |
| 0.5818        | 12.68 | 1800 | 0.7458          | 0.9367 |
| 0.5437        | 13.38 | 1900 | 0.6843          | 0.9374 |
| 0.4759        | 14.08 | 2000 | 0.6411          | 0.9357 |
| 0.4674        | 14.79 | 2100 | 0.6010          | 0.9388 |
| 0.4305        | 15.49 | 2200 | 0.5682          | 0.9427 |
| 0.3862        | 16.2  | 2300 | 0.5369          | 0.9424 |
| 0.3564        | 16.9  | 2400 | 0.5208          | 0.9412 |
| 0.3292        | 17.61 | 2500 | 0.5022          | 0.9424 |
| 0.3237        | 18.31 | 2600 | 0.4903          | 0.9450 |
| 0.3187        | 19.01 | 2700 | 0.4807          | 0.9460 |
| 0.317         | 19.72 | 2800 | 0.4772          | 0.9465 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3