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# scenario-kd-from-scratch-silver-data-tyqiangz-multilingual-sentiments-english-mo

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: 17.8682
- Accuracy: 0.4660
- F1: 0.4644

## 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        | 1.72  | 100  | 13.4193         | 0.3765   | 0.2933 |
| No log        | 3.45  | 200  | 13.2682         | 0.3302   | 0.1659 |
| No log        | 5.17  | 300  | 12.9515         | 0.3981   | 0.3561 |
| No log        | 6.9   | 400  | 14.2435         | 0.4907   | 0.4868 |
| 12.0501       | 8.62  | 500  | 14.4132         | 0.4846   | 0.4833 |
| 12.0501       | 10.34 | 600  | 17.5253         | 0.3735   | 0.3234 |
| 12.0501       | 12.07 | 700  | 14.7342         | 0.4815   | 0.4750 |
| 12.0501       | 13.79 | 800  | 19.8334         | 0.3951   | 0.3751 |
| 12.0501       | 15.52 | 900  | 19.2609         | 0.4660   | 0.4332 |
| 3.4682        | 17.24 | 1000 | 18.8041         | 0.4414   | 0.4257 |
| 3.4682        | 18.97 | 1100 | 19.8361         | 0.4321   | 0.4112 |
| 3.4682        | 20.69 | 1200 | 18.2141         | 0.4784   | 0.4805 |
| 3.4682        | 22.41 | 1300 | 20.4826         | 0.4321   | 0.4009 |
| 3.4682        | 24.14 | 1400 | 18.9589         | 0.4691   | 0.4591 |
| 1.5933        | 25.86 | 1500 | 17.4688         | 0.4537   | 0.4469 |
| 1.5933        | 27.59 | 1600 | 18.2712         | 0.4660   | 0.4659 |
| 1.5933        | 29.31 | 1700 | 19.6104         | 0.4630   | 0.4538 |
| 1.5933        | 31.03 | 1800 | 17.4482         | 0.4630   | 0.4667 |
| 1.5933        | 32.76 | 1900 | 17.8682         | 0.4660   | 0.4644 |


### 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-english-mo", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:multilingual-sentiments base_model:xlm-roberta-base license:mit endpoints_compatible region:us