
<!-- 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-pre-finetune-div-2-data-tyqiangz-multilingual-sentiments-en

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: 3.2146
- Accuracy: 0.6080
- F1: 0.5977

## 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  | 0.8685          | 0.6204   | 0.6227 |
| No log        | 3.45  | 200  | 0.9198          | 0.6512   | 0.6415 |
| No log        | 5.17  | 300  | 1.2662          | 0.5957   | 0.5961 |
| No log        | 6.9   | 400  | 1.5007          | 0.6142   | 0.6190 |
| 0.5169        | 8.62  | 500  | 2.1495          | 0.6080   | 0.5945 |
| 0.5169        | 10.34 | 600  | 2.2519          | 0.6265   | 0.6221 |
| 0.5169        | 12.07 | 700  | 2.0479          | 0.6142   | 0.6124 |
| 0.5169        | 13.79 | 800  | 2.4999          | 0.6235   | 0.6210 |
| 0.5169        | 15.52 | 900  | 2.4666          | 0.6358   | 0.6288 |
| 0.0877        | 17.24 | 1000 | 2.5752          | 0.6173   | 0.5987 |
| 0.0877        | 18.97 | 1100 | 2.7212          | 0.6235   | 0.6248 |
| 0.0877        | 20.69 | 1200 | 2.5686          | 0.6389   | 0.6400 |
| 0.0877        | 22.41 | 1300 | 2.8150          | 0.6265   | 0.6271 |
| 0.0877        | 24.14 | 1400 | 2.9070          | 0.6327   | 0.6312 |
| 0.0516        | 25.86 | 1500 | 2.6489          | 0.6173   | 0.6168 |
| 0.0516        | 27.59 | 1600 | 3.0738          | 0.6142   | 0.6183 |
| 0.0516        | 29.31 | 1700 | 3.2146          | 0.6080   | 0.5977 |


### 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-non-kd-from-pre-finetune-div-2-data-tyqiangz-multilingual-sentiments-en", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:multilingual-sentiments base_model:xlm-roberta-base license:mit endpoints_compatible region:us