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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_pan_loss_2e-05
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. -->
# xlm-roberta-base_pan_loss_2e-05
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: 0.0216
- Spearman Corr: 0.7776
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| No log | 0.85 | 200 | 0.0210 | 0.7733 |
| No log | 1.69 | 400 | 0.0215 | 0.7798 |
| 0.0009 | 2.54 | 600 | 0.0219 | 0.7770 |
| 0.0009 | 3.38 | 800 | 0.0212 | 0.7807 |
| 0.0006 | 4.23 | 1000 | 0.0224 | 0.7806 |
| 0.0006 | 5.07 | 1200 | 0.0210 | 0.7800 |
| 0.0006 | 5.92 | 1400 | 0.0208 | 0.7799 |
| 0.0004 | 6.77 | 1600 | 0.0214 | 0.7793 |
| 0.0004 | 7.61 | 1800 | 0.0216 | 0.7795 |
| 0.0003 | 8.46 | 2000 | 0.0207 | 0.7819 |
| 0.0003 | 9.3 | 2200 | 0.0209 | 0.7826 |
| 0.0004 | 10.15 | 2400 | 0.0209 | 0.7793 |
| 0.0004 | 10.99 | 2600 | 0.0207 | 0.7804 |
| 0.0004 | 11.84 | 2800 | 0.0210 | 0.7808 |
| 0.0004 | 12.68 | 3000 | 0.0216 | 0.7776 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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