---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-CDF-EN-FROM-EN-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-EN-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: 25.8673
- Accuracy: 0.3959
- F1: 0.3838

## 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  | 21.4869         | 0.3399   | 0.2229 |
| No log        | 3.45  | 200  | 21.6387         | 0.3699   | 0.3103 |
| No log        | 5.17  | 300  | 21.3511         | 0.3907   | 0.3762 |
| No log        | 6.9   | 400  | 21.9513         | 0.3968   | 0.3590 |
| 22.0328       | 8.62  | 500  | 21.5760         | 0.4048   | 0.3925 |
| 22.0328       | 10.34 | 600  | 21.8280         | 0.4259   | 0.4236 |
| 22.0328       | 12.07 | 700  | 22.1319         | 0.4096   | 0.4040 |
| 22.0328       | 13.79 | 800  | 23.1465         | 0.3884   | 0.3602 |
| 22.0328       | 15.52 | 900  | 23.6087         | 0.3907   | 0.3658 |
| 15.8082       | 17.24 | 1000 | 24.1019         | 0.3968   | 0.3767 |
| 15.8082       | 18.97 | 1100 | 24.2550         | 0.3973   | 0.3850 |
| 15.8082       | 20.69 | 1200 | 23.9667         | 0.4092   | 0.4043 |
| 15.8082       | 22.41 | 1300 | 25.2656         | 0.4145   | 0.4010 |
| 15.8082       | 24.14 | 1400 | 26.0200         | 0.3893   | 0.3638 |
| 11.3074       | 25.86 | 1500 | 25.2350         | 0.4101   | 0.3887 |
| 11.3074       | 27.59 | 1600 | 25.8133         | 0.4012   | 0.3853 |
| 11.3074       | 29.31 | 1700 | 25.8673         | 0.3959   | 0.3838 |


### Framework versions

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