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# scenario-non-kd-from-pre-finetune-div-2-data-tyqiangz-multilingual-sentiments-ma

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: 2.2224
- Accuracy: 0.6985
- F1: 0.6661

## 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  | 0.7717          | 0.6189   | 0.5854 |
| No log        | 1.36  | 200  | 0.8048          | 0.6468   | 0.6332 |
| No log        | 2.04  | 300  | 0.7043          | 0.6647   | 0.6364 |
| No log        | 2.72  | 400  | 0.7412          | 0.6438   | 0.6260 |
| 0.6872        | 3.4   | 500  | 0.7609          | 0.6955   | 0.6748 |
| 0.6872        | 4.08  | 600  | 0.8408          | 0.6876   | 0.6697 |
| 0.6872        | 4.76  | 700  | 0.8482          | 0.6846   | 0.6562 |
| 0.6872        | 5.44  | 800  | 0.9626          | 0.6876   | 0.6719 |
| 0.6872        | 6.12  | 900  | 1.0625          | 0.7154   | 0.6978 |
| 0.3167        | 6.8   | 1000 | 1.1384          | 0.6836   | 0.6588 |
| 0.3167        | 7.48  | 1100 | 1.1296          | 0.7035   | 0.6766 |
| 0.3167        | 8.16  | 1200 | 1.4336          | 0.6736   | 0.6469 |
| 0.3167        | 8.84  | 1300 | 1.4899          | 0.6736   | 0.6529 |
| 0.3167        | 9.52  | 1400 | 1.2895          | 0.7154   | 0.6956 |
| 0.1513        | 10.2  | 1500 | 1.5986          | 0.7114   | 0.6769 |
| 0.1513        | 10.88 | 1600 | 1.7920          | 0.6905   | 0.6679 |
| 0.1513        | 11.56 | 1700 | 1.6600          | 0.6975   | 0.6608 |
| 0.1513        | 12.24 | 1800 | 1.6425          | 0.6915   | 0.6704 |
| 0.1513        | 12.93 | 1900 | 1.8379          | 0.6915   | 0.6745 |
| 0.0825        | 13.61 | 2000 | 1.6874          | 0.6925   | 0.6748 |
| 0.0825        | 14.29 | 2100 | 1.8852          | 0.6955   | 0.6725 |
| 0.0825        | 14.97 | 2200 | 1.9019          | 0.7075   | 0.6864 |
| 0.0825        | 15.65 | 2300 | 2.1659          | 0.7065   | 0.6808 |
| 0.0825        | 16.33 | 2400 | 2.2224          | 0.6985   | 0.6661 |


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