---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr0.0001_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_lr0.0001_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: 0.0468
- Spearman Corr: 0.0355

## 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        | 1.55  | 200  | 0.0533          | -0.1261       |
| 0.0648        | 3.1   | 400  | 0.0450          | 0.0883        |
| 0.0593        | 4.65  | 600  | 0.0551          | nan           |
| 0.0584        | 6.2   | 800  | 0.0453          | 0.0647        |
| 0.0584        | 7.75  | 1000 | 0.0535          | 0.1302        |
| 0.0584        | 9.3   | 1200 | 0.0447          | 0.1247        |
| 0.0564        | 10.85 | 1400 | 0.0568          | 0.0145        |
| 0.0564        | 12.4  | 1600 | 0.0447          | nan           |
| 0.056         | 13.95 | 1800 | 0.0491          | 0.0365        |
| 0.056         | 15.5  | 2000 | 0.0472          | nan           |
| 0.0564        | 17.05 | 2200 | 0.0473          | nan           |
| 0.0555        | 18.6  | 2400 | 0.0457          | nan           |
| 0.0555        | 20.16 | 2600 | 0.0472          | -0.0083       |
| 0.0555        | 21.71 | 2800 | 0.0473          | nan           |
| 0.055         | 23.26 | 3000 | 0.0447          | 0.0283        |
| 0.0549        | 24.81 | 3200 | 0.0468          | 0.0355        |


### Framework versions

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