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# xlm-roberta-base_amh_corr_2e-05

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: 0.0246
- Spearman Corr: 0.7671

## 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        | 0.9   | 200  | 0.0252          | 0.7645        |
| No log        | 1.81  | 400  | 0.0277          | 0.7586        |
| 0.0072        | 2.71  | 600  | 0.0302          | 0.7579        |
| 0.0072        | 3.62  | 800  | 0.0253          | 0.7618        |
| 0.0057        | 4.52  | 1000 | 0.0234          | 0.7674        |
| 0.0057        | 5.43  | 1200 | 0.0248          | 0.7638        |
| 0.0047        | 6.33  | 1400 | 0.0280          | 0.7582        |
| 0.0047        | 7.24  | 1600 | 0.0251          | 0.7655        |
| 0.0039        | 8.14  | 1800 | 0.0259          | 0.7661        |
| 0.0039        | 9.05  | 2000 | 0.0251          | 0.7691        |
| 0.0039        | 9.95  | 2200 | 0.0258          | 0.7684        |
| 0.0035        | 10.86 | 2400 | 0.0237          | 0.7680        |
| 0.0035        | 11.76 | 2600 | 0.0249          | 0.7622        |
| 0.0031        | 12.67 | 2800 | 0.0240          | 0.7656        |
| 0.0031        | 13.57 | 3000 | 0.0248          | 0.7668        |
| 0.0028        | 14.48 | 3200 | 0.0246          | 0.7688        |
| 0.0028        | 15.38 | 3400 | 0.0241          | 0.7670        |
| 0.0026        | 16.29 | 3600 | 0.0268          | 0.7693        |
| 0.0026        | 17.19 | 3800 | 0.0239          | 0.7690        |
| 0.0024        | 18.1  | 4000 | 0.0257          | 0.7716        |
| 0.0024        | 19.0  | 4200 | 0.0234          | 0.7717        |
| 0.0024        | 19.91 | 4400 | 0.0235          | 0.7690        |
| 0.0022        | 20.81 | 4600 | 0.0238          | 0.7711        |
| 0.0022        | 21.72 | 4800 | 0.0245          | 0.7694        |
| 0.0021        | 22.62 | 5000 | 0.0238          | 0.7680        |
| 0.0021        | 23.53 | 5200 | 0.0254          | 0.7674        |
| 0.0019        | 24.43 | 5400 | 0.0247          | 0.7679        |
| 0.0019        | 25.34 | 5600 | 0.0246          | 0.7671        |


### 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_amh_corr_2e-05", "results": []}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us