---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only_beta-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-MSV-D2_data-cl-cardiff_cl_only_beta-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: 15.7103
- Accuracy: 0.4028
- F1: 0.4028

## 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: 6666
- 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        | 1.09  | 250  | 11.8668         | 0.3897   | 0.3820 |
| 13.776        | 2.17  | 500  | 11.3224         | 0.3873   | 0.3811 |
| 13.776        | 3.26  | 750  | 10.7331         | 0.3881   | 0.3824 |
| 11.4609       | 4.35  | 1000 | 11.7060         | 0.4035   | 0.4015 |
| 11.4609       | 5.43  | 1250 | 11.1579         | 0.3997   | 0.3802 |
| 9.9802        | 6.52  | 1500 | 11.6003         | 0.4066   | 0.4061 |
| 9.9802        | 7.61  | 1750 | 11.6088         | 0.4059   | 0.4048 |
| 8.6874        | 8.7   | 2000 | 11.9784         | 0.3904   | 0.3814 |
| 8.6874        | 9.78  | 2250 | 12.2923         | 0.4113   | 0.4097 |
| 7.5941        | 10.87 | 2500 | 13.1464         | 0.3858   | 0.3823 |
| 7.5941        | 11.96 | 2750 | 12.8350         | 0.3966   | 0.3946 |
| 6.5229        | 13.04 | 3000 | 13.1611         | 0.3850   | 0.3819 |
| 6.5229        | 14.13 | 3250 | 14.1517         | 0.4005   | 0.3995 |
| 5.6501        | 15.22 | 3500 | 14.0929         | 0.4005   | 0.3930 |
| 5.6501        | 16.3  | 3750 | 14.1956         | 0.4074   | 0.4070 |
| 4.9968        | 17.39 | 4000 | 13.8417         | 0.4043   | 0.4040 |
| 4.9968        | 18.48 | 4250 | 14.3873         | 0.3897   | 0.3879 |
| 4.4769        | 19.57 | 4500 | 15.4822         | 0.4244   | 0.4226 |
| 4.4769        | 20.65 | 4750 | 15.1566         | 0.3958   | 0.3952 |
| 3.9676        | 21.74 | 5000 | 14.8283         | 0.4159   | 0.4135 |
| 3.9676        | 22.83 | 5250 | 15.2368         | 0.3927   | 0.3928 |
| 3.6886        | 23.91 | 5500 | 15.4609         | 0.4005   | 0.4006 |
| 3.6886        | 25.0  | 5750 | 14.7384         | 0.4059   | 0.4038 |
| 3.4119        | 26.09 | 6000 | 15.4645         | 0.3858   | 0.3857 |
| 3.4119        | 27.17 | 6250 | 15.9168         | 0.3974   | 0.3967 |
| 3.1245        | 28.26 | 6500 | 15.4980         | 0.3920   | 0.3923 |
| 3.1245        | 29.35 | 6750 | 15.7103         | 0.4028   | 0.4028 |


### Framework versions

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