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# scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-large

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the indolem_sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6221
- Accuracy: 0.9123
- F1: 0.8583

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.44  | 200  | 0.4767          | 0.7569   | 0.3310 |
| No log        | 0.88  | 400  | 0.3503          | 0.8822   | 0.7983 |
| 0.4797        | 1.32  | 600  | 0.3976          | 0.9098   | 0.8302 |
| 0.4797        | 1.76  | 800  | 0.3545          | 0.9173   | 0.8584 |
| 0.3498        | 2.2   | 1000 | 0.3955          | 0.9173   | 0.8596 |
| 0.3498        | 2.64  | 1200 | 0.3558          | 0.9298   | 0.8803 |
| 0.3498        | 3.08  | 1400 | 0.4563          | 0.9198   | 0.8621 |
| 0.2444        | 3.52  | 1600 | 0.4079          | 0.9223   | 0.8714 |
| 0.2444        | 3.96  | 1800 | 0.4416          | 0.9198   | 0.8609 |
| 0.1788        | 4.4   | 2000 | 0.5722          | 0.9073   | 0.8452 |
| 0.1788        | 4.84  | 2200 | 0.6618          | 0.8972   | 0.8392 |
| 0.1788        | 5.27  | 2400 | 0.4956          | 0.9298   | 0.875  |
| 0.128         | 5.71  | 2600 | 0.6221          | 0.9123   | 0.8583 |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["indolem_sentiment"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-large", "model-index": [{"name": "scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-large", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "indolem_sentiment", "type": "indolem_sentiment", "config": "indolem_sentiment_nusantara_text", "split": "validation", "args": "indolem_sentiment_nusantara_text"}, "metrics": [{"type": "accuracy", "value": 0.9122807017543859, "name": "Accuracy"}, {"type": "f1", "value": 0.8582995951417003, "name": "F1"}]}]}]}
transformers pytorch xlm-roberta text-classification generated_from_trainer dataset:indolem_sentiment base_model:xlm-roberta-large license:mit model-index autotrain_compatible endpoints_compatible region:us