---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr0.0001_seed42_basic_original_kin-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_lr0.0001_seed42_basic_original_kin-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: 0.0490
- Spearman Corr: 0.0413

## 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        | 1.59  | 200  | 0.0521          | 0.0335        |
| 0.0641        | 3.19  | 400  | 0.0491          | 0.0517        |
| 0.0587        | 4.78  | 600  | 0.0499          | 0.0819        |
| 0.0574        | 6.37  | 800  | 0.0551          | -0.0486       |
| 0.0575        | 7.97  | 1000 | 0.0498          | 0.0406        |
| 0.0575        | 9.56  | 1200 | 0.0525          | -0.0395       |
| 0.0566        | 11.16 | 1400 | 0.0499          | 0.0551        |
| 0.0564        | 12.75 | 1600 | 0.0509          | 0.0279        |
| 0.0557        | 14.34 | 1800 | 0.0513          | -0.0191       |
| 0.0558        | 15.94 | 2000 | 0.0516          | 0.0619        |
| 0.0558        | 17.53 | 2200 | 0.0511          | 0.0308        |
| 0.0555        | 19.12 | 2400 | 0.0490          | 0.0413        |


### Framework versions

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