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# xlmroberta_mixup_back

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0611
- Spearman Corr: 0.2466

## 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: 36
- eval_batch_size: 144
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 72
- 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        | 0.11  | 20   | 0.0701          | -0.0323       |
| No log        | 0.21  | 40   | 0.0613          | 0.0336        |
| No log        | 0.32  | 60   | 0.0755          | 0.0627        |
| No log        | 0.43  | 80   | 0.1200          | 0.1902        |
| No log        | 0.53  | 100  | 0.0961          | 0.1906        |
| No log        | 0.64  | 120  | 0.0973          | 0.1694        |
| No log        | 0.75  | 140  | 0.0918          | 0.2296        |
| No log        | 0.86  | 160  | 0.0614          | 0.2128        |
| No log        | 0.96  | 180  | 0.0607          | 0.2090        |
| No log        | 1.07  | 200  | 0.0581          | 0.2252        |
| No log        | 1.18  | 220  | 0.0651          | 0.2340        |
| No log        | 1.28  | 240  | 0.0556          | 0.2590        |
| No log        | 1.39  | 260  | 0.1081          | 0.2593        |
| No log        | 1.5   | 280  | 0.0724          | 0.2920        |
| No log        | 1.6   | 300  | 0.1213          | 0.2862        |
| No log        | 1.71  | 320  | 0.0617          | 0.2879        |
| No log        | 1.82  | 340  | 0.0774          | 0.2620        |
| No log        | 1.93  | 360  | 0.0571          | 0.2518        |
| 0.0972        | 2.03  | 380  | 0.0565          | 0.2471        |
| 0.0972        | 2.14  | 400  | 0.0531          | 0.2608        |
| 0.0972        | 2.25  | 420  | 0.0728          | 0.2815        |
| 0.0972        | 2.35  | 440  | 0.0733          | 0.2658        |
| 0.0972        | 2.46  | 460  | 0.0672          | 0.2942        |
| 0.0972        | 2.57  | 480  | 0.2626          | 0.2995        |
| 0.0972        | 2.67  | 500  | 0.0733          | 0.3036        |
| 0.0972        | 2.78  | 520  | 0.0647          | 0.2741        |
| 0.0972        | 2.89  | 540  | 0.0594          | 0.2604        |
| 0.0972        | 2.99  | 560  | 0.0594          | 0.2439        |
| 0.0972        | 3.1   | 580  | 0.0685          | 0.2463        |
| 0.0972        | 3.21  | 600  | 0.0779          | 0.2668        |
| 0.0972        | 3.32  | 620  | 0.0559          | 0.2760        |
| 0.0972        | 3.42  | 640  | 0.0845          | 0.2826        |
| 0.0972        | 3.53  | 660  | 0.1213          | 0.2937        |
| 0.0972        | 3.64  | 680  | 0.0748          | 0.2798        |
| 0.0972        | 3.74  | 700  | 0.0835          | 0.2542        |
| 0.0972        | 3.85  | 720  | 0.0565          | 0.2417        |
| 0.0972        | 3.96  | 740  | 0.0763          | 0.2658        |
| 0.064         | 4.06  | 760  | 0.0750          | 0.2533        |
| 0.064         | 4.17  | 780  | 0.0611          | 0.2466        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

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