---
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