---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr2e-05_seed42_basic_original_esp-hau-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-hau-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: 0.0304
- Spearman Corr: 0.7478

## 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        | 1.45  | 200  | 0.0245          | 0.7170        |
| 0.0409        | 2.91  | 400  | 0.0266          | 0.7475        |
| 0.0242        | 4.36  | 600  | 0.0272          | 0.7548        |
| 0.0242        | 5.82  | 800  | 0.0273          | 0.7521        |
| 0.0183        | 7.27  | 1000 | 0.0274          | 0.7521        |
| 0.0142        | 8.73  | 1200 | 0.0282          | 0.7645        |
| 0.0111        | 10.18 | 1400 | 0.0263          | 0.7587        |
| 0.0111        | 11.64 | 1600 | 0.0302          | 0.7507        |
| 0.0093        | 13.09 | 1800 | 0.0268          | 0.7509        |
| 0.0076        | 14.55 | 2000 | 0.0306          | 0.7383        |
| 0.0062        | 16.0  | 2200 | 0.0304          | 0.7478        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2