---
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: 1.0967
- F1: 0.8702

## 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.747         | 1.39  | 500   | 1.0303          | 0.5703 |
| 0.5618        | 2.78  | 1000  | 0.9201          | 0.6479 |
| 0.3695        | 4.17  | 1500  | 0.8216          | 0.6990 |
| 0.3392        | 5.56  | 2000  | 0.7637          | 0.7335 |
| 0.2638        | 6.94  | 2500  | 0.8244          | 0.7678 |
| 0.1907        | 8.33  | 3000  | 0.7912          | 0.7979 |
| 0.1661        | 9.72  | 3500  | 0.8266          | 0.7835 |
| 0.1073        | 11.11 | 4000  | 0.8120          | 0.8139 |
| 0.1265        | 12.5  | 4500  | 0.8336          | 0.8344 |
| 0.0481        | 13.89 | 5000  | 0.8240          | 0.8518 |
| 0.0646        | 15.28 | 5500  | 0.9290          | 0.8333 |
| 0.0846        | 16.67 | 6000  | 0.9176          | 0.8461 |
| 0.0228        | 18.06 | 6500  | 0.9600          | 0.8529 |
| 0.0696        | 19.44 | 7000  | 0.9769          | 0.8525 |
| 0.0614        | 20.83 | 7500  | 0.9944          | 0.8545 |
| 0.0173        | 22.22 | 8000  | 1.0110          | 0.8550 |
| 0.004         | 23.61 | 8500  | 1.0140          | 0.8417 |
| 0.0032        | 25.0  | 9000  | 1.0771          | 0.8314 |
| 0.0453        | 26.39 | 9500  | 1.0173          | 0.8424 |
| 0.0471        | 27.78 | 10000 | 1.0068          | 0.8652 |
| 0.0128        | 29.17 | 10500 | 1.0595          | 0.8658 |
| 0.0027        | 30.56 | 11000 | 1.0596          | 0.8506 |
| 0.0198        | 31.94 | 11500 | 1.0468          | 0.8593 |
| 0.0027        | 33.33 | 12000 | 1.0537          | 0.8693 |
| 0.0114        | 34.72 | 12500 | 1.0512          | 0.8620 |
| 0.015         | 36.11 | 13000 | 1.0425          | 0.8813 |
| 0.005         | 37.5  | 13500 | 1.1092          | 0.8749 |
| 0.0038        | 38.89 | 14000 | 1.0829          | 0.8637 |
| 0.0096        | 40.28 | 14500 | 1.0902          | 0.8794 |
| 0.0007        | 41.67 | 15000 | 1.0994          | 0.8651 |
| 0.0109        | 43.06 | 15500 | 1.0957          | 0.8782 |
| 0.0026        | 44.44 | 16000 | 1.0997          | 0.8643 |
| 0.0061        | 45.83 | 16500 | 1.0853          | 0.8672 |
| 0.0005        | 47.22 | 17000 | 1.1082          | 0.8694 |
| 0.0005        | 48.61 | 17500 | 1.1016          | 0.8696 |
| 0.0028        | 50.0  | 18000 | 1.0967          | 0.8702 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0