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# xlm-roberta-base_latin_amh-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: 0.0299
- Spearman Corr: 0.7565

## 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        | 0.52  | 200  | 0.0314          | 0.7022        |
| No log        | 1.04  | 400  | 0.0254          | 0.7158        |
| No log        | 1.55  | 600  | 0.0281          | 0.7444        |
| 0.0413        | 2.07  | 800  | 0.0301          | 0.7603        |
| 0.0413        | 2.59  | 1000 | 0.0316          | 0.7524        |
| 0.0413        | 3.11  | 1200 | 0.0362          | 0.7638        |
| 0.0413        | 3.63  | 1400 | 0.0275          | 0.7505        |
| 0.0266        | 4.15  | 1600 | 0.0299          | 0.7588        |
| 0.0266        | 4.66  | 1800 | 0.0334          | 0.7610        |
| 0.0266        | 5.18  | 2000 | 0.0317          | 0.7595        |
| 0.0266        | 5.7   | 2200 | 0.0274          | 0.7570        |
| 0.0202        | 6.22  | 2400 | 0.0250          | 0.7680        |
| 0.0202        | 6.74  | 2600 | 0.0300          | 0.7780        |
| 0.0202        | 7.25  | 2800 | 0.0321          | 0.7649        |
| 0.0202        | 7.77  | 3000 | 0.0306          | 0.7616        |
| 0.0155        | 8.29  | 3200 | 0.0335          | 0.7627        |
| 0.0155        | 8.81  | 3400 | 0.0293          | 0.7541        |
| 0.0155        | 9.33  | 3600 | 0.0286          | 0.7529        |
| 0.0155        | 9.84  | 3800 | 0.0283          | 0.7582        |
| 0.012         | 10.36 | 4000 | 0.0283          | 0.7551        |
| 0.012         | 10.88 | 4200 | 0.0299          | 0.7565        |


### 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_latin_amh-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