---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_ary_loss_0.0001
  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_ary_loss_0.0001

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: 0.0476
- Spearman Corr: -0.0518

## 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: 0.0001
- 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        | 0.9   | 200  | 0.0463          | nan           |
| No log        | 1.8   | 400  | 0.0463          | nan           |
| 0.0485        | 2.7   | 600  | 0.0481          | nan           |
| 0.0485        | 3.6   | 800  | 0.0470          | nan           |
| 0.0488        | 4.5   | 1000 | 0.0472          | -0.0282       |
| 0.0488        | 5.41  | 1200 | 0.0465          | nan           |
| 0.0485        | 6.31  | 1400 | 0.0465          | nan           |
| 0.0485        | 7.21  | 1600 | 0.0462          | nan           |
| 0.0489        | 8.11  | 1800 | 0.0470          | nan           |
| 0.0489        | 9.01  | 2000 | 0.0463          | -0.0105       |
| 0.0489        | 9.91  | 2200 | 0.0464          | nan           |
| 0.0485        | 10.81 | 2400 | 0.0464          | nan           |
| 0.0485        | 11.71 | 2600 | 0.0464          | nan           |
| 0.0485        | 12.61 | 2800 | 0.0465          | nan           |
| 0.0485        | 13.51 | 3000 | 0.0464          | 0.0548        |
| 0.0485        | 14.41 | 3200 | 0.0476          | -0.0518       |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2