---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_latin_kin-amh-eng_train_loss
  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_latin_kin-amh-eng_train_loss

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: 0.0326
- Spearman Corr: 0.7395

## 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: 2e-05
- 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        | 0.59  | 200  | 0.0303          | 0.6125        |
| No log        | 1.17  | 400  | 0.0269          | 0.6780        |
| No log        | 1.76  | 600  | 0.0393          | 0.6855        |
| 0.036         | 2.35  | 800  | 0.0338          | 0.7111        |
| 0.036         | 2.93  | 1000 | 0.0303          | 0.6886        |
| 0.036         | 3.52  | 1200 | 0.0327          | 0.7025        |
| 0.0243        | 4.11  | 1400 | 0.0269          | 0.7220        |
| 0.0243        | 4.69  | 1600 | 0.0287          | 0.7246        |
| 0.0243        | 5.28  | 1800 | 0.0260          | 0.7336        |
| 0.0243        | 5.87  | 2000 | 0.0266          | 0.7234        |
| 0.0185        | 6.45  | 2200 | 0.0252          | 0.7347        |
| 0.0185        | 7.04  | 2400 | 0.0281          | 0.7276        |
| 0.0185        | 7.62  | 2600 | 0.0294          | 0.7298        |
| 0.0141        | 8.21  | 2800 | 0.0274          | 0.7219        |
| 0.0141        | 8.8   | 3000 | 0.0285          | 0.7260        |
| 0.0141        | 9.38  | 3200 | 0.0276          | 0.7315        |
| 0.0141        | 9.97  | 3400 | 0.0291          | 0.7329        |
| 0.0109        | 10.56 | 3600 | 0.0310          | 0.7339        |
| 0.0109        | 11.14 | 3800 | 0.0326          | 0.7395        |


### Framework versions

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