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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr5e-06_seed42_basic_original_amh-esp-eng_train
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_lr5e-06_seed42_basic_original_amh-esp-eng_train
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: 0.0208
- Spearman Corr: 0.7694
## 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-06
- 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 | 1.59 | 200 | 0.0178 | 0.7278 |
| 0.0931 | 3.17 | 400 | 0.0197 | 0.7452 |
| 0.0276 | 4.76 | 600 | 0.0183 | 0.7513 |
| 0.0243 | 6.35 | 800 | 0.0158 | 0.7667 |
| 0.0243 | 7.94 | 1000 | 0.0182 | 0.7692 |
| 0.021 | 9.52 | 1200 | 0.0189 | 0.7704 |
| 0.0192 | 11.11 | 1400 | 0.0184 | 0.7656 |
| 0.0176 | 12.7 | 1600 | 0.0226 | 0.7691 |
| 0.0163 | 14.29 | 1800 | 0.0225 | 0.7696 |
| 0.0163 | 15.87 | 2000 | 0.0207 | 0.7718 |
| 0.0156 | 17.46 | 2200 | 0.0242 | 0.7697 |
| 0.0143 | 19.05 | 2400 | 0.0207 | 0.7664 |
| 0.0138 | 20.63 | 2600 | 0.0201 | 0.7721 |
| 0.013 | 22.22 | 2800 | 0.0208 | 0.7694 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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