---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr0.0001_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_lr0.0001_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: 0.0399
- Spearman Corr: 0.0444

## 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        | 1.75  | 200  | 0.0384          | -0.0298       |
| 0.0606        | 3.51  | 400  | 0.0428          | 0.0555        |
| 0.0542        | 5.26  | 600  | 0.0399          | 0.1268        |
| 0.0522        | 7.02  | 800  | 0.0373          | 0.2132        |
| 0.0519        | 8.77  | 1000 | 0.0399          | 0.0780        |
| 0.0516        | 10.53 | 1200 | 0.0391          | nan           |
| 0.051         | 12.28 | 1400 | 0.0380          | -0.0558       |
| 0.0505        | 14.04 | 1600 | 0.0375          | 0.0632        |
| 0.0505        | 15.79 | 1800 | 0.0390          | 0.0344        |
| 0.0505        | 17.54 | 2000 | 0.0395          | 0.0575        |
| 0.0498        | 19.3  | 2200 | 0.0397          | 0.0553        |
| 0.0494        | 21.05 | 2400 | 0.0381          | 0.0810        |
| 0.0492        | 22.81 | 2600 | 0.0383          | nan           |
| 0.0489        | 24.56 | 2800 | 0.0399          | 0.0444        |


### Framework versions

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