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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr2e-05_seed42_basic_original_esp-kin-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_lr2e-05_seed42_basic_original_esp-kin-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: 0.0284
- Spearman Corr: 0.7240
## 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 | 1.63 | 200 | 0.0303 | 0.6450 |
| 0.0362 | 3.27 | 400 | 0.0274 | 0.6899 |
| 0.0204 | 4.9 | 600 | 0.0238 | 0.6971 |
| 0.0161 | 6.53 | 800 | 0.0278 | 0.7107 |
| 0.0124 | 8.16 | 1000 | 0.0294 | 0.7245 |
| 0.0124 | 9.8 | 1200 | 0.0284 | 0.7332 |
| 0.0093 | 11.43 | 1400 | 0.0294 | 0.7160 |
| 0.0075 | 13.06 | 1600 | 0.0275 | 0.7203 |
| 0.0061 | 14.69 | 1800 | 0.0267 | 0.7250 |
| 0.0053 | 16.33 | 2000 | 0.0308 | 0.7266 |
| 0.0053 | 17.96 | 2200 | 0.0316 | 0.7213 |
| 0.0049 | 19.59 | 2400 | 0.0293 | 0.7216 |
| 0.0042 | 21.22 | 2600 | 0.0284 | 0.7240 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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