
<!-- 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_spearman_corr

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: 0.0290
- Spearman Corr: 0.7237

## 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  | 0.0279          | 0.6205        |
| No log        | 1.17  | 400  | 0.0265          | 0.6575        |
| No log        | 1.76  | 600  | 0.0380          | 0.6844        |
| 0.0373        | 2.35  | 800  | 0.0307          | 0.7164        |
| 0.0373        | 2.93  | 1000 | 0.0340          | 0.6776        |
| 0.0373        | 3.52  | 1200 | 0.0312          | 0.7050        |
| 0.0244        | 4.11  | 1400 | 0.0298          | 0.7134        |
| 0.0244        | 4.69  | 1600 | 0.0285          | 0.7190        |
| 0.0244        | 5.28  | 1800 | 0.0278          | 0.7217        |
| 0.0244        | 5.87  | 2000 | 0.0298          | 0.7006        |
| 0.0185        | 6.45  | 2200 | 0.0258          | 0.7114        |
| 0.0185        | 7.04  | 2400 | 0.0295          | 0.7164        |
| 0.0185        | 7.62  | 2600 | 0.0333          | 0.7204        |
| 0.0144        | 8.21  | 2800 | 0.0300          | 0.7201        |
| 0.0144        | 8.8   | 3000 | 0.0326          | 0.7290        |
| 0.0144        | 9.38  | 3200 | 0.0292          | 0.7114        |
| 0.0144        | 9.97  | 3400 | 0.0289          | 0.7052        |
| 0.0109        | 10.56 | 3600 | 0.0336          | 0.7125        |
| 0.0109        | 11.14 | 3800 | 0.0307          | 0.7147        |
| 0.0109        | 11.73 | 4000 | 0.0308          | 0.7174        |
| 0.0086        | 12.32 | 4200 | 0.0285          | 0.7217        |
| 0.0086        | 12.9  | 4400 | 0.0288          | 0.7083        |
| 0.0086        | 13.49 | 4600 | 0.0290          | 0.7237        |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "base_model": "FacebookAI/xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base_latin_kin-amh-eng_train_spearman_corr", "results": []}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us