---
license: mit
base_model: haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- hate_speech_filipino
metrics:
- accuracy
- f1
model-index:
- name: scenario-non-kd-from-post-finetune-div-2-data-hate_speech_filipino-model-haryoaw
  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. -->

# scenario-non-kd-from-post-finetune-div-2-data-hate_speech_filipino-model-haryoaw

This model is a fine-tuned version of [haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base](https://huggingface.co/haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base) on the hate_speech_filipino dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3495
- Accuracy: 0.7779
- F1: 0.7601

## 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: 6969

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.32  | 100  | 0.5751          | 0.7339   | 0.7510 |
| No log        | 0.64  | 200  | 0.5171          | 0.7717   | 0.7450 |
| No log        | 0.96  | 300  | 0.4969          | 0.7784   | 0.7539 |
| No log        | 1.28  | 400  | 0.5408          | 0.7819   | 0.7548 |
| 0.4175        | 1.6   | 500  | 0.5410          | 0.7635   | 0.7597 |
| 0.4175        | 1.92  | 600  | 0.5166          | 0.7767   | 0.7324 |
| 0.4175        | 2.24  | 700  | 0.5823          | 0.7651   | 0.7450 |
| 0.4175        | 2.56  | 800  | 0.5731          | 0.7672   | 0.7293 |
| 0.4175        | 2.88  | 900  | 0.6860          | 0.7769   | 0.7458 |
| 0.2936        | 3.19  | 1000 | 0.7409          | 0.7684   | 0.7659 |
| 0.2936        | 3.51  | 1100 | 0.6544          | 0.7772   | 0.7487 |
| 0.2936        | 3.83  | 1200 | 0.6719          | 0.7604   | 0.7613 |
| 0.2936        | 4.15  | 1300 | 0.8242          | 0.7781   | 0.7471 |
| 0.2936        | 4.47  | 1400 | 0.8741          | 0.7838   | 0.7472 |
| 0.199         | 4.79  | 1500 | 0.7415          | 0.7755   | 0.7509 |
| 0.199         | 5.11  | 1600 | 0.9389          | 0.7897   | 0.7615 |
| 0.199         | 5.43  | 1700 | 0.7985          | 0.7840   | 0.7693 |
| 0.199         | 5.75  | 1800 | 0.9223          | 0.7741   | 0.7600 |
| 0.199         | 6.07  | 1900 | 1.0076          | 0.7727   | 0.7667 |
| 0.1553        | 6.39  | 2000 | 0.8541          | 0.7800   | 0.7682 |
| 0.1553        | 6.71  | 2100 | 0.9460          | 0.7810   | 0.7600 |
| 0.1553        | 7.03  | 2200 | 1.0575          | 0.7791   | 0.7571 |
| 0.1553        | 7.35  | 2300 | 1.0487          | 0.7687   | 0.7657 |
| 0.1553        | 7.67  | 2400 | 0.8495          | 0.7732   | 0.7568 |
| 0.1316        | 7.99  | 2500 | 0.9467          | 0.7812   | 0.7658 |
| 0.1316        | 8.31  | 2600 | 1.0491          | 0.7722   | 0.7611 |
| 0.1316        | 8.63  | 2700 | 1.0363          | 0.7691   | 0.7275 |
| 0.1316        | 8.95  | 2800 | 0.9130          | 0.7758   | 0.7448 |
| 0.1316        | 9.27  | 2900 | 1.4607          | 0.7717   | 0.7562 |
| 0.1137        | 9.58  | 3000 | 1.1874          | 0.7727   | 0.7567 |
| 0.1137        | 9.9   | 3100 | 1.1752          | 0.7836   | 0.7672 |
| 0.1137        | 10.22 | 3200 | 1.3495          | 0.7779   | 0.7601 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3