---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr5e-06_seed42_basic_original_amh-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_amh-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: 0.0289
- Spearman Corr: 0.7801

## 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        | 1.55  | 200  | 0.0251          | 0.7275        |
| 0.0824        | 3.1   | 400  | 0.0250          | 0.7584        |
| 0.0309        | 4.65  | 600  | 0.0251          | 0.7713        |
| 0.0251        | 6.2   | 800  | 0.0254          | 0.7824        |
| 0.0251        | 7.75  | 1000 | 0.0271          | 0.7791        |
| 0.0222        | 9.3   | 1200 | 0.0258          | 0.7837        |
| 0.0199        | 10.85 | 1400 | 0.0302          | 0.7791        |
| 0.0182        | 12.4  | 1600 | 0.0244          | 0.7815        |
| 0.0166        | 13.95 | 1800 | 0.0299          | 0.7793        |
| 0.0166        | 15.5  | 2000 | 0.0256          | 0.7818        |
| 0.0154        | 17.05 | 2200 | 0.0275          | 0.7880        |
| 0.0145        | 18.6  | 2400 | 0.0283          | 0.7780        |
| 0.0138        | 20.16 | 2600 | 0.0299          | 0.7810        |
| 0.0138        | 21.71 | 2800 | 0.0298          | 0.7834        |
| 0.013         | 23.26 | 3000 | 0.0279          | 0.7813        |
| 0.0125        | 24.81 | 3200 | 0.0279          | 0.7802        |
| 0.0119        | 26.36 | 3400 | 0.0281          | 0.7790        |
| 0.0117        | 27.91 | 3600 | 0.0289          | 0.7801        |


### Framework versions

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