---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_hau_loss_5e-06
  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_hau_loss_5e-06

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: 0.0248
- Spearman Corr: 0.7591

## 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        | 0.95  | 200  | 0.0249          | 0.7564        |
| No log        | 1.91  | 400  | 0.0258          | 0.7583        |
| 0.0014        | 2.86  | 600  | 0.0239          | 0.7618        |
| 0.0014        | 3.82  | 800  | 0.0246          | 0.7601        |
| 0.0013        | 4.77  | 1000 | 0.0242          | 0.7588        |
| 0.0013        | 5.73  | 1200 | 0.0241          | 0.7574        |
| 0.0013        | 6.68  | 1400 | 0.0248          | 0.7605        |
| 0.0013        | 7.64  | 1600 | 0.0255          | 0.7623        |
| 0.0014        | 8.59  | 1800 | 0.0247          | 0.7585        |
| 0.0014        | 9.55  | 2000 | 0.0252          | 0.7582        |
| 0.0014        | 10.5  | 2200 | 0.0248          | 0.7591        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2