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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_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
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