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---
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_alpha-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_alpha-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: 15.6971
- Accuracy: 0.4105
- F1: 0.4078
## 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: 2222
- 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 | 12.5527 | 0.3779 | 0.3087 |
| No log | 3.45 | 200 | 12.9504 | 0.3757 | 0.3098 |
| No log | 5.17 | 300 | 12.9363 | 0.3884 | 0.3458 |
| No log | 6.9 | 400 | 13.3706 | 0.3951 | 0.3814 |
| 13.0874 | 8.62 | 500 | 13.5495 | 0.3849 | 0.3679 |
| 13.0874 | 10.34 | 600 | 14.1809 | 0.3739 | 0.3340 |
| 13.0874 | 12.07 | 700 | 13.9627 | 0.3814 | 0.3774 |
| 13.0874 | 13.79 | 800 | 14.6754 | 0.3907 | 0.3806 |
| 13.0874 | 15.52 | 900 | 14.1172 | 0.4136 | 0.4087 |
| 9.6129 | 17.24 | 1000 | 14.2157 | 0.3871 | 0.3752 |
| 9.6129 | 18.97 | 1100 | 14.6144 | 0.4030 | 0.3987 |
| 9.6129 | 20.69 | 1200 | 15.2951 | 0.3942 | 0.3947 |
| 9.6129 | 22.41 | 1300 | 15.0876 | 0.3933 | 0.3839 |
| 9.6129 | 24.14 | 1400 | 15.3136 | 0.4004 | 0.3987 |
| 7.2639 | 25.86 | 1500 | 15.5724 | 0.4061 | 0.4007 |
| 7.2639 | 27.59 | 1600 | 15.8778 | 0.3986 | 0.3984 |
| 7.2639 | 29.31 | 1700 | 15.6971 | 0.4105 | 0.4078 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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