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# xlm-roberta-base_esp_corr_2e-05

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: 0.0215
- Spearman Corr: 0.7827

## 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        | 0.94  | 200  | 0.0216          | 0.7772        |
| No log        | 1.89  | 400  | 0.0220          | 0.7787        |
| 0.001         | 2.83  | 600  | 0.0229          | 0.7785        |
| 0.001         | 3.77  | 800  | 0.0229          | 0.7756        |
| 0.001         | 4.72  | 1000 | 0.0222          | 0.7790        |
| 0.001         | 5.66  | 1200 | 0.0210          | 0.7827        |
| 0.0009        | 6.6   | 1400 | 0.0222          | 0.7784        |
| 0.0009        | 7.55  | 1600 | 0.0214          | 0.7788        |
| 0.0008        | 8.49  | 1800 | 0.0227          | 0.7798        |
| 0.0008        | 9.43  | 2000 | 0.0218          | 0.7792        |
| 0.0008        | 10.38 | 2200 | 0.0215          | 0.7804        |
| 0.0008        | 11.32 | 2400 | 0.0208          | 0.7798        |
| 0.0007        | 12.26 | 2600 | 0.0220          | 0.7833        |
| 0.0007        | 13.21 | 2800 | 0.0209          | 0.7820        |
| 0.0007        | 14.15 | 3000 | 0.0212          | 0.7833        |
| 0.0007        | 15.09 | 3200 | 0.0213          | 0.7800        |
| 0.0006        | 16.04 | 3400 | 0.0215          | 0.7810        |
| 0.0006        | 16.98 | 3600 | 0.0221          | 0.7811        |
| 0.0006        | 17.92 | 3800 | 0.0215          | 0.7813        |
| 0.0006        | 18.87 | 4000 | 0.0216          | 0.7822        |
| 0.0006        | 19.81 | 4200 | 0.0215          | 0.7827        |


### 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_esp_corr_2e-05", "results": []}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us