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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_beta-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_beta-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: 15.8985
- Accuracy: 0.4109
- F1: 0.4052
## 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: 6666
- 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 | 12.7770 | 0.3289 | 0.2140 |
| No log | 3.45 | 200 | 12.5133 | 0.3611 | 0.3597 |
| No log | 5.17 | 300 | 12.8380 | 0.3854 | 0.3580 |
| No log | 6.9 | 400 | 12.8508 | 0.4061 | 0.4051 |
| 13.1287 | 8.62 | 500 | 13.5318 | 0.4017 | 0.3945 |
| 13.1287 | 10.34 | 600 | 13.1743 | 0.3973 | 0.3971 |
| 13.1287 | 12.07 | 700 | 13.8236 | 0.4114 | 0.4114 |
| 13.1287 | 13.79 | 800 | 14.0940 | 0.3854 | 0.3717 |
| 13.1287 | 15.52 | 900 | 14.3671 | 0.4008 | 0.3905 |
| 9.0164 | 17.24 | 1000 | 14.6749 | 0.4078 | 0.3961 |
| 9.0164 | 18.97 | 1100 | 14.8097 | 0.3924 | 0.3850 |
| 9.0164 | 20.69 | 1200 | 15.4684 | 0.3867 | 0.3827 |
| 9.0164 | 22.41 | 1300 | 15.2537 | 0.4078 | 0.4008 |
| 9.0164 | 24.14 | 1400 | 16.0142 | 0.4039 | 0.3995 |
| 6.3951 | 25.86 | 1500 | 15.7916 | 0.4105 | 0.4106 |
| 6.3951 | 27.59 | 1600 | 16.2415 | 0.3827 | 0.3681 |
| 6.3951 | 29.31 | 1700 | 15.8985 | 0.4109 | 0.4052 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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