---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr2e-05_seed42_basic_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_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: 0.0266
- Spearman Corr: 0.8166

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| 0.0451        | 2.33  | 200  | 0.0186          | 0.7909        |
| 0.0202        | 4.65  | 400  | 0.0282          | 0.8043        |
| 0.0153        | 6.98  | 600  | 0.0223          | 0.8111        |
| 0.0117        | 9.3   | 800  | 0.0272          | 0.8021        |
| 0.0096        | 11.63 | 1000 | 0.0267          | 0.8105        |
| 0.007         | 13.95 | 1200 | 0.0253          | 0.8226        |
| 0.0061        | 16.28 | 1400 | 0.0269          | 0.8107        |
| 0.0052        | 18.6  | 1600 | 0.0252          | 0.8172        |
| 0.0047        | 20.93 | 1800 | 0.0264          | 0.8179        |
| 0.0044        | 23.26 | 2000 | 0.0247          | 0.8206        |
| 0.004         | 25.58 | 2200 | 0.0266          | 0.8166        |


### Framework versions

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