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# scenario-KD-PR-MSV-D2-data-cl-massive-all_1.1

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7236
- Accuracy: 0.6988
- F1: 0.6534

## 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: 99
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.8854        | 0.56  | 5000  | 3.1282          | 0.6529   | 0.5784 |
| 1.2048        | 1.11  | 10000 | 2.8835          | 0.6771   | 0.6110 |
| 1.0223        | 1.67  | 15000 | 2.8778          | 0.6799   | 0.6228 |
| 0.7641        | 2.22  | 20000 | 2.8453          | 0.6829   | 0.6235 |
| 0.7116        | 2.78  | 25000 | 2.9294          | 0.6820   | 0.6396 |
| 0.5803        | 3.33  | 30000 | 2.7768          | 0.6919   | 0.6491 |
| 0.5358        | 3.89  | 35000 | 2.7771          | 0.6938   | 0.6489 |
| 0.4575        | 4.45  | 40000 | 2.7236          | 0.6988   | 0.6534 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy", "f1"], "base_model": "FacebookAI/xlm-roberta-base", "model-index": [{"name": "scenario-KD-PR-MSV-D2-data-cl-massive-all_1.1", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:massive base_model:FacebookAI/xlm-roberta-base license:mit endpoints_compatible region:us