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# scenario-kd-from-scratch-silver-data-tyqiangz-multilingual-sentiments-malay-mode

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the multilingual-sentiments dataset.
It achieves the following results on the evaluation set:
- Loss: 14.5594
- Accuracy: 0.6080
- F1: 0.5395

## 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        | 0.68  | 100  | 13.6758         | 0.4766   | 0.3271 |
| No log        | 1.36  | 200  | 11.9485         | 0.5303   | 0.3802 |
| No log        | 2.04  | 300  | 11.7084         | 0.5622   | 0.4064 |
| No log        | 2.72  | 400  | 11.1698         | 0.5821   | 0.5355 |
| 12.9548       | 3.4   | 500  | 10.4061         | 0.6249   | 0.5964 |
| 12.9548       | 4.08  | 600  | 11.3083         | 0.6209   | 0.5827 |
| 12.9548       | 4.76  | 700  | 11.9240         | 0.6209   | 0.5794 |
| 12.9548       | 5.44  | 800  | 14.9044         | 0.5771   | 0.5038 |
| 12.9548       | 6.12  | 900  | 12.3307         | 0.6308   | 0.5696 |
| 5.7647        | 6.8   | 1000 | 11.9038         | 0.6308   | 0.5862 |
| 5.7647        | 7.48  | 1100 | 12.3580         | 0.6368   | 0.6095 |
| 5.7647        | 8.16  | 1200 | 13.7124         | 0.6289   | 0.5518 |
| 5.7647        | 8.84  | 1300 | 12.8972         | 0.6199   | 0.5953 |
| 5.7647        | 9.52  | 1400 | 14.2245         | 0.6040   | 0.5771 |
| 2.8315        | 10.2  | 1500 | 15.7431         | 0.5980   | 0.5671 |
| 2.8315        | 10.88 | 1600 | 14.1603         | 0.6199   | 0.5619 |
| 2.8315        | 11.56 | 1700 | 12.6210         | 0.6428   | 0.6158 |
| 2.8315        | 12.24 | 1800 | 15.0500         | 0.6119   | 0.5477 |
| 2.8315        | 12.93 | 1900 | 13.8910         | 0.6279   | 0.5400 |
| 2.0743        | 13.61 | 2000 | 14.2150         | 0.6279   | 0.6067 |
| 2.0743        | 14.29 | 2100 | 13.1529         | 0.6478   | 0.6087 |
| 2.0743        | 14.97 | 2200 | 13.5424         | 0.6358   | 0.6119 |
| 2.0743        | 15.65 | 2300 | 13.8704         | 0.6289   | 0.5959 |
| 2.0743        | 16.33 | 2400 | 14.4637         | 0.6119   | 0.5909 |
| 1.7132        | 17.01 | 2500 | 13.2986         | 0.6328   | 0.5824 |
| 1.7132        | 17.69 | 2600 | 13.5977         | 0.6318   | 0.6104 |
| 1.7132        | 18.37 | 2700 | 12.9483         | 0.6517   | 0.6299 |
| 1.7132        | 19.05 | 2800 | 13.6398         | 0.6289   | 0.5999 |
| 1.7132        | 19.73 | 2900 | 13.0128         | 0.6498   | 0.6151 |
| 1.5334        | 20.41 | 3000 | 13.3749         | 0.6478   | 0.6017 |
| 1.5334        | 21.09 | 3100 | 13.8551         | 0.6428   | 0.6138 |
| 1.5334        | 21.77 | 3200 | 13.7106         | 0.6348   | 0.5988 |
| 1.5334        | 22.45 | 3300 | 13.3699         | 0.6378   | 0.6068 |
| 1.5334        | 23.13 | 3400 | 13.0654         | 0.6458   | 0.5763 |
| 1.3343        | 23.81 | 3500 | 12.9332         | 0.6418   | 0.6108 |
| 1.3343        | 24.49 | 3600 | 14.2306         | 0.6209   | 0.5948 |
| 1.3343        | 25.17 | 3700 | 13.2935         | 0.6299   | 0.6053 |
| 1.3343        | 25.85 | 3800 | 14.0929         | 0.6279   | 0.5748 |
| 1.3343        | 26.53 | 3900 | 13.7570         | 0.6308   | 0.5814 |
| 1.1461        | 27.21 | 4000 | 13.2298         | 0.6318   | 0.5924 |
| 1.1461        | 27.89 | 4100 | 13.9291         | 0.6299   | 0.6149 |
| 1.1461        | 28.57 | 4200 | 14.5594         | 0.6080   | 0.5395 |


### 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": ["multilingual-sentiments"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-kd-from-scratch-silver-data-tyqiangz-multilingual-sentiments-malay-mode", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:multilingual-sentiments base_model:xlm-roberta-base license:mit endpoints_compatible region:us