---
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