---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only_gamma-jason
  results: []
---

<!-- 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-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only_gamma-jason

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 16.3831
- Accuracy: 0.3955
- F1: 0.3889

## 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: 88458
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.72  | 100  | 12.6768         | 0.3280   | 0.2299 |
| No log        | 3.45  | 200  | 12.6987         | 0.3836   | 0.3671 |
| No log        | 5.17  | 300  | 12.8320         | 0.3858   | 0.3602 |
| No log        | 6.9   | 400  | 13.1201         | 0.3620   | 0.3230 |
| 13.3889       | 8.62  | 500  | 13.0591         | 0.3920   | 0.3845 |
| 13.3889       | 10.34 | 600  | 14.1639         | 0.4004   | 0.3832 |
| 13.3889       | 12.07 | 700  | 14.7159         | 0.3810   | 0.3536 |
| 13.3889       | 13.79 | 800  | 14.3341         | 0.3907   | 0.3815 |
| 13.3889       | 15.52 | 900  | 14.9958         | 0.3792   | 0.3564 |
| 9.5405        | 17.24 | 1000 | 14.4299         | 0.3902   | 0.3887 |
| 9.5405        | 18.97 | 1100 | 15.3658         | 0.3999   | 0.3973 |
| 9.5405        | 20.69 | 1200 | 15.1707         | 0.3990   | 0.3940 |
| 9.5405        | 22.41 | 1300 | 15.8556         | 0.3955   | 0.3816 |
| 9.5405        | 24.14 | 1400 | 15.7963         | 0.3915   | 0.3825 |
| 6.9987        | 25.86 | 1500 | 15.8559         | 0.4056   | 0.4012 |
| 6.9987        | 27.59 | 1600 | 16.1802         | 0.3854   | 0.3757 |
| 6.9987        | 29.31 | 1700 | 16.3831         | 0.3955   | 0.3889 |


### Framework versions

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