---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr5e-06_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_lr5e-06_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: 0.0334
- Spearman Corr: 0.7247

## 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  | 0.0366          | 0.6063        |
| 0.0656        | 3.19  | 400  | 0.0336          | 0.6631        |
| 0.0346        | 4.78  | 600  | 0.0303          | 0.6995        |
| 0.029         | 6.37  | 800  | 0.0311          | 0.7091        |
| 0.0253        | 7.97  | 1000 | 0.0298          | 0.7144        |
| 0.0253        | 9.56  | 1200 | 0.0322          | 0.7142        |
| 0.0222        | 11.16 | 1400 | 0.0303          | 0.7187        |
| 0.0202        | 12.75 | 1600 | 0.0316          | 0.7215        |
| 0.0183        | 14.34 | 1800 | 0.0325          | 0.7235        |
| 0.0174        | 15.94 | 2000 | 0.0298          | 0.7277        |
| 0.0174        | 17.53 | 2200 | 0.0315          | 0.7305        |
| 0.0162        | 19.12 | 2400 | 0.0338          | 0.7305        |
| 0.015         | 20.72 | 2600 | 0.0320          | 0.7264        |
| 0.0145        | 22.31 | 2800 | 0.0319          | 0.7278        |
| 0.014         | 23.9  | 3000 | 0.0334          | 0.7247        |


### Framework versions

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