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# xlmroberta_clir_back

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0152
- Spearman Corr: 0.8972

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| No log        | 1.0   | 206  | 0.0300          | 0.6949        |
| 0.041         | 2.0   | 413  | 0.0230          | 0.7671        |
| 0.041         | 3.0   | 619  | 0.0183          | 0.8169        |
| 0.0219        | 4.0   | 826  | 0.0154          | 0.8516        |
| 0.0219        | 5.0   | 1032 | 0.0146          | 0.8698        |
| 0.0133        | 6.0   | 1239 | 0.0150          | 0.8869        |
| 0.0133        | 7.0   | 1445 | 0.0152          | 0.8972        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

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