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# xlm-roberta-base_latin_original_amh-esp-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: 0.0233
- Spearman Corr: 0.7706

## 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        | 1.59  | 200  | 0.0202          | 0.7613        |
| 0.0371        | 3.17  | 400  | 0.0169          | 0.7592        |
| 0.0203        | 4.76  | 600  | 0.0212          | 0.7674        |
| 0.0151        | 6.35  | 800  | 0.0208          | 0.7667        |
| 0.0151        | 7.94  | 1000 | 0.0226          | 0.7734        |
| 0.0116        | 9.52  | 1200 | 0.0230          | 0.7745        |
| 0.0092        | 11.11 | 1400 | 0.0236          | 0.7687        |
| 0.0077        | 12.7  | 1600 | 0.0206          | 0.7650        |
| 0.0061        | 14.29 | 1800 | 0.0217          | 0.7693        |
| 0.0061        | 15.87 | 2000 | 0.0263          | 0.7671        |
| 0.0053        | 17.46 | 2200 | 0.0239          | 0.7674        |
| 0.0046        | 19.05 | 2400 | 0.0242          | 0.7598        |
| 0.004         | 20.63 | 2600 | 0.0223          | 0.7751        |
| 0.0038        | 22.22 | 2800 | 0.0231          | 0.7665        |
| 0.0038        | 23.81 | 3000 | 0.0245          | 0.7654        |
| 0.0035        | 25.4  | 3200 | 0.0236          | 0.7731        |
| 0.0032        | 26.98 | 3400 | 0.0236          | 0.7695        |
| 0.0031        | 28.57 | 3600 | 0.0233          | 0.7706        |


### 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_original_amh-esp-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