---
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_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-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_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: 15.8985
- Accuracy: 0.4109
- F1: 0.4052

## 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        | 1.72  | 100  | 12.7770         | 0.3289   | 0.2140 |
| No log        | 3.45  | 200  | 12.5133         | 0.3611   | 0.3597 |
| No log        | 5.17  | 300  | 12.8380         | 0.3854   | 0.3580 |
| No log        | 6.9   | 400  | 12.8508         | 0.4061   | 0.4051 |
| 13.1287       | 8.62  | 500  | 13.5318         | 0.4017   | 0.3945 |
| 13.1287       | 10.34 | 600  | 13.1743         | 0.3973   | 0.3971 |
| 13.1287       | 12.07 | 700  | 13.8236         | 0.4114   | 0.4114 |
| 13.1287       | 13.79 | 800  | 14.0940         | 0.3854   | 0.3717 |
| 13.1287       | 15.52 | 900  | 14.3671         | 0.4008   | 0.3905 |
| 9.0164        | 17.24 | 1000 | 14.6749         | 0.4078   | 0.3961 |
| 9.0164        | 18.97 | 1100 | 14.8097         | 0.3924   | 0.3850 |
| 9.0164        | 20.69 | 1200 | 15.4684         | 0.3867   | 0.3827 |
| 9.0164        | 22.41 | 1300 | 15.2537         | 0.4078   | 0.4008 |
| 9.0164        | 24.14 | 1400 | 16.0142         | 0.4039   | 0.3995 |
| 6.3951        | 25.86 | 1500 | 15.7916         | 0.4105   | 0.4106 |
| 6.3951        | 27.59 | 1600 | 16.2415         | 0.3827   | 0.3681 |
| 6.3951        | 29.31 | 1700 | 15.8985         | 0.4109   | 0.4052 |


### Framework versions

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