---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr5e-06_seed42_basic_original_kin-amh-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-amh-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: 0.0312
- Spearman Corr: 0.7479

## 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        | 1.75  | 200  | 0.0278          | 0.6150        |
| 0.0637        | 3.51  | 400  | 0.0254          | 0.6786        |
| 0.0312        | 5.26  | 600  | 0.0284          | 0.7074        |
| 0.0249        | 7.02  | 800  | 0.0320          | 0.7195        |
| 0.0199        | 8.77  | 1000 | 0.0344          | 0.7285        |
| 0.0189        | 10.53 | 1200 | 0.0303          | 0.7318        |
| 0.0167        | 12.28 | 1400 | 0.0299          | 0.7356        |
| 0.0154        | 14.04 | 1600 | 0.0319          | 0.7411        |
| 0.0154        | 15.79 | 1800 | 0.0304          | 0.7382        |
| 0.0141        | 17.54 | 2000 | 0.0327          | 0.7460        |
| 0.0134        | 19.3  | 2200 | 0.0305          | 0.7507        |
| 0.0123        | 21.05 | 2400 | 0.0312          | 0.7479        |


### Framework versions

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