---
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: 0.5941
- F1: 0.2075

## 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: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | F1     |
|:-------------:|:-----:|:------:|:---------------:|:------:|
| 1.6114        | 0.18  | 4000   | 2.8696          | 0.0216 |
| 1.175         | 0.37  | 8000   | 2.4185          | 0.0298 |
| 1.0297        | 0.55  | 12000  | 2.2393          | 0.0265 |
| 0.9481        | 0.74  | 16000  | 2.0412          | 0.0359 |
| 0.907         | 0.92  | 20000  | 1.9175          | 0.0369 |
| 0.8091        | 1.11  | 24000  | 1.7551          | 0.0542 |
| 0.7541        | 1.29  | 28000  | 1.6911          | 0.0638 |
| 0.7476        | 1.48  | 32000  | 1.5999          | 0.0736 |
| 0.6812        | 1.66  | 36000  | 1.5595          | 0.0887 |
| 0.6615        | 1.85  | 40000  | 1.4151          | 0.1002 |
| 0.5681        | 2.03  | 44000  | 1.3710          | 0.1013 |
| 0.5088        | 2.22  | 48000  | 1.2370          | 0.1176 |
| 0.5355        | 2.4   | 52000  | 1.1219          | 0.1327 |
| 0.4965        | 2.59  | 56000  | 1.1772          | 0.1381 |
| 0.4671        | 2.77  | 60000  | 1.0597          | 0.1549 |
| 0.4902        | 2.95  | 64000  | 1.0120          | 0.1549 |
| 0.4143        | 3.14  | 68000  | 0.8947          | 0.1836 |
| 0.3805        | 3.32  | 72000  | 0.8788          | 0.1731 |
| 0.3766        | 3.51  | 76000  | 0.8115          | 0.1762 |
| 0.3691        | 3.69  | 80000  | 0.8016          | 0.1800 |
| 0.3698        | 3.88  | 84000  | 0.7637          | 0.1857 |
| 0.3368        | 4.06  | 88000  | 0.7051          | 0.1933 |
| 0.3267        | 4.25  | 92000  | 0.6571          | 0.1969 |
| 0.34          | 4.43  | 96000  | 0.6427          | 0.1980 |
| 0.2947        | 4.62  | 100000 | 0.6451          | 0.2029 |
| 0.3118        | 4.8   | 104000 | 0.6006          | 0.2018 |
| 0.2873        | 4.99  | 108000 | 0.5941          | 0.2075 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.0