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# xlm-roberta-base_esp-kin-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: 0.0306
- Spearman Corr: 0.6931

## 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        | 0.54  | 200  | 0.0281          | 0.6201        |
| No log        | 1.09  | 400  | 0.0245          | 0.6554        |
| No log        | 1.63  | 600  | 0.0287          | 0.6675        |
| 0.0336        | 2.18  | 800  | 0.0326          | 0.6610        |
| 0.0336        | 2.72  | 1000 | 0.0292          | 0.6750        |
| 0.0336        | 3.27  | 1200 | 0.0294          | 0.6797        |
| 0.0336        | 3.81  | 1400 | 0.0276          | 0.6976        |
| 0.0203        | 4.35  | 1600 | 0.0276          | 0.7022        |
| 0.0203        | 4.9   | 1800 | 0.0259          | 0.6997        |
| 0.0203        | 5.44  | 2000 | 0.0283          | 0.7034        |
| 0.0203        | 5.99  | 2200 | 0.0279          | 0.7174        |
| 0.0146        | 6.53  | 2400 | 0.0310          | 0.6980        |
| 0.0146        | 7.07  | 2600 | 0.0303          | 0.6995        |
| 0.0146        | 7.62  | 2800 | 0.0285          | 0.6961        |
| 0.0105        | 8.16  | 3000 | 0.0372          | 0.6989        |
| 0.0105        | 8.71  | 3200 | 0.0284          | 0.6933        |
| 0.0105        | 9.25  | 3400 | 0.0351          | 0.7014        |
| 0.0105        | 9.8   | 3600 | 0.0331          | 0.7006        |
| 0.008         | 10.34 | 3800 | 0.0306          | 0.6931        |


### 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-kin-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