metadata
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_alpha-jason
results: []
scenario-KD-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only_alpha-jason
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 25.0852
- Accuracy: 0.3990
- F1: 0.3923
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 | 21.4007 | 0.3351 | 0.1783 |
| No log | 3.45 | 200 | 21.2647 | 0.3602 | 0.2851 |
| No log | 5.17 | 300 | 21.7287 | 0.3836 | 0.3173 |
| No log | 6.9 | 400 | 22.0257 | 0.3779 | 0.3535 |
| 22.4551 | 8.62 | 500 | 21.9464 | 0.3761 | 0.3596 |
| 22.4551 | 10.34 | 600 | 22.5105 | 0.3849 | 0.3792 |
| 22.4551 | 12.07 | 700 | 23.3230 | 0.3743 | 0.3466 |
| 22.4551 | 13.79 | 800 | 23.3751 | 0.3739 | 0.3490 |
| 22.4551 | 15.52 | 900 | 22.6748 | 0.3990 | 0.3990 |
| 17.2022 | 17.24 | 1000 | 23.5182 | 0.3902 | 0.3782 |
| 17.2022 | 18.97 | 1100 | 23.4775 | 0.3836 | 0.3785 |
| 17.2022 | 20.69 | 1200 | 23.9951 | 0.3893 | 0.3789 |
| 17.2022 | 22.41 | 1300 | 24.6740 | 0.3770 | 0.3500 |
| 17.2022 | 24.14 | 1400 | 25.2132 | 0.3593 | 0.3287 |
| 13.0792 | 25.86 | 1500 | 24.6053 | 0.3924 | 0.3825 |
| 13.0792 | 27.59 | 1600 | 25.0044 | 0.3854 | 0.3766 |
| 13.0792 | 29.31 | 1700 | 25.0852 | 0.3990 | 0.3923 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3