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# xlm-roberta-base_kin-hau-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: 0.0363
- Spearman Corr: 0.7305

## 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        | 0.53  | 200  | 0.0444          | 0.6614        |
| No log        | 1.06  | 400  | 0.0370          | 0.6910        |
| No log        | 1.6   | 600  | 0.0453          | 0.6924        |
| 0.0401        | 2.13  | 800  | 0.0353          | 0.6988        |
| 0.0401        | 2.66  | 1000 | 0.0359          | 0.7081        |
| 0.0401        | 3.19  | 1200 | 0.0368          | 0.7005        |
| 0.0401        | 3.72  | 1400 | 0.0356          | 0.7153        |
| 0.0257        | 4.26  | 1600 | 0.0320          | 0.7303        |
| 0.0257        | 4.79  | 1800 | 0.0304          | 0.7219        |
| 0.0257        | 5.32  | 2000 | 0.0431          | 0.7236        |
| 0.0257        | 5.85  | 2200 | 0.0335          | 0.7280        |
| 0.019         | 6.38  | 2400 | 0.0313          | 0.7130        |
| 0.019         | 6.91  | 2600 | 0.0309          | 0.7331        |
| 0.019         | 7.45  | 2800 | 0.0308          | 0.7338        |
| 0.019         | 7.98  | 3000 | 0.0329          | 0.7391        |
| 0.0143        | 8.51  | 3200 | 0.0340          | 0.7305        |
| 0.0143        | 9.04  | 3400 | 0.0358          | 0.7315        |
| 0.0143        | 9.57  | 3600 | 0.0347          | 0.7422        |
| 0.011         | 10.11 | 3800 | 0.0378          | 0.7414        |
| 0.011         | 10.64 | 4000 | 0.0295          | 0.7383        |
| 0.011         | 11.17 | 4200 | 0.0341          | 0.7410        |
| 0.011         | 11.7  | 4400 | 0.0404          | 0.7404        |
| 0.0086        | 12.23 | 4600 | 0.0343          | 0.7345        |
| 0.0086        | 12.77 | 4800 | 0.0333          | 0.7352        |
| 0.0086        | 13.3  | 5000 | 0.0376          | 0.7313        |
| 0.0086        | 13.83 | 5200 | 0.0363          | 0.7305        |


### 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_kin-hau-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