---
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_delta-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_delta-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: 16.6296
- Accuracy: 0.3717
- F1: 0.3536

## 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: 7777
- 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  | 12.7327         | 0.3325   | 0.1812 |
| No log        | 3.45  | 200  | 12.8292         | 0.3761   | 0.3217 |
| No log        | 5.17  | 300  | 12.9466         | 0.3823   | 0.3524 |
| No log        | 6.9   | 400  | 12.8228         | 0.3867   | 0.3832 |
| 13.1958       | 8.62  | 500  | 13.3388         | 0.3823   | 0.3761 |
| 13.1958       | 10.34 | 600  | 14.0438         | 0.3920   | 0.3814 |
| 13.1958       | 12.07 | 700  | 15.2932         | 0.3792   | 0.3468 |
| 13.1958       | 13.79 | 800  | 15.4804         | 0.3735   | 0.3295 |
| 13.1958       | 15.52 | 900  | 16.1070         | 0.3818   | 0.3438 |
| 8.893         | 17.24 | 1000 | 14.9589         | 0.3805   | 0.3482 |
| 8.893         | 18.97 | 1100 | 15.2843         | 0.3849   | 0.3704 |
| 8.893         | 20.69 | 1200 | 15.6003         | 0.3942   | 0.3873 |
| 8.893         | 22.41 | 1300 | 15.5817         | 0.4087   | 0.4044 |
| 8.893         | 24.14 | 1400 | 16.1571         | 0.3898   | 0.3802 |
| 6.538         | 25.86 | 1500 | 16.3557         | 0.3907   | 0.3763 |
| 6.538         | 27.59 | 1600 | 16.4529         | 0.3889   | 0.3753 |
| 6.538         | 29.31 | 1700 | 16.6296         | 0.3717   | 0.3536 |


### Framework versions

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