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# furina_seed42_eng_esp_hau

This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0133
- Spearman Corr: 0.8711

## 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        | 0.54  | 200   | 0.0318          | 0.6526        |
| No log        | 1.08  | 400   | 0.0280          | 0.7226        |
| No log        | 1.62  | 600   | 0.0253          | 0.7469        |
| 0.0472        | 2.15  | 800   | 0.0230          | 0.7583        |
| 0.0472        | 2.69  | 1000  | 0.0219          | 0.7738        |
| 0.0472        | 3.23  | 1200  | 0.0222          | 0.7832        |
| 0.0472        | 3.77  | 1400  | 0.0206          | 0.7891        |
| 0.0218        | 4.31  | 1600  | 0.0207          | 0.7936        |
| 0.0218        | 4.85  | 1800  | 0.0198          | 0.8013        |
| 0.0218        | 5.38  | 2000  | 0.0187          | 0.8112        |
| 0.0218        | 5.92  | 2200  | 0.0192          | 0.8131        |
| 0.0153        | 6.46  | 2400  | 0.0180          | 0.8233        |
| 0.0153        | 7.0   | 2600  | 0.0193          | 0.8265        |
| 0.0153        | 7.54  | 2800  | 0.0183          | 0.8305        |
| 0.0111        | 8.08  | 3000  | 0.0171          | 0.8339        |
| 0.0111        | 8.61  | 3200  | 0.0175          | 0.8337        |
| 0.0111        | 9.15  | 3400  | 0.0166          | 0.8350        |
| 0.0111        | 9.69  | 3600  | 0.0165          | 0.8362        |
| 0.0085        | 10.23 | 3800  | 0.0161          | 0.8436        |
| 0.0085        | 10.77 | 4000  | 0.0169          | 0.8442        |
| 0.0085        | 11.31 | 4200  | 0.0164          | 0.8414        |
| 0.0085        | 11.84 | 4400  | 0.0152          | 0.8492        |
| 0.0068        | 12.38 | 4600  | 0.0152          | 0.8477        |
| 0.0068        | 12.92 | 4800  | 0.0158          | 0.8512        |
| 0.0068        | 13.46 | 5000  | 0.0150          | 0.8542        |
| 0.0057        | 14.0  | 5200  | 0.0149          | 0.8564        |
| 0.0057        | 14.54 | 5400  | 0.0159          | 0.8555        |
| 0.0057        | 15.07 | 5600  | 0.0146          | 0.8581        |
| 0.0057        | 15.61 | 5800  | 0.0143          | 0.8576        |
| 0.0049        | 16.15 | 6000  | 0.0143          | 0.8587        |
| 0.0049        | 16.69 | 6200  | 0.0146          | 0.8593        |
| 0.0049        | 17.23 | 6400  | 0.0158          | 0.8597        |
| 0.0049        | 17.77 | 6600  | 0.0140          | 0.8611        |
| 0.0043        | 18.3  | 6800  | 0.0147          | 0.8610        |
| 0.0043        | 18.84 | 7000  | 0.0141          | 0.8634        |
| 0.0043        | 19.38 | 7200  | 0.0143          | 0.8635        |
| 0.0043        | 19.92 | 7400  | 0.0143          | 0.8647        |
| 0.0038        | 20.46 | 7600  | 0.0138          | 0.8650        |
| 0.0038        | 21.0  | 7800  | 0.0142          | 0.8657        |
| 0.0038        | 21.53 | 8000  | 0.0138          | 0.8655        |
| 0.0035        | 22.07 | 8200  | 0.0142          | 0.8663        |
| 0.0035        | 22.61 | 8400  | 0.0137          | 0.8664        |
| 0.0035        | 23.15 | 8600  | 0.0138          | 0.8669        |
| 0.0035        | 23.69 | 8800  | 0.0140          | 0.8694        |
| 0.0033        | 24.23 | 9000  | 0.0134          | 0.8690        |
| 0.0033        | 24.76 | 9200  | 0.0146          | 0.8683        |
| 0.0033        | 25.3  | 9400  | 0.0138          | 0.8678        |
| 0.0033        | 25.84 | 9600  | 0.0134          | 0.8701        |
| 0.003         | 26.38 | 9800  | 0.0136          | 0.8702        |
| 0.003         | 26.92 | 10000 | 0.0135          | 0.8713        |
| 0.003         | 27.46 | 10200 | 0.0133          | 0.8704        |
| 0.0029        | 27.99 | 10400 | 0.0135          | 0.8714        |
| 0.0029        | 28.53 | 10600 | 0.0133          | 0.8711        |


### Framework versions

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

{"tags": ["generated_from_trainer"], "base_model": "yihongLiu/furina", "model-index": [{"name": "furina_seed42_eng_esp_hau", "results": []}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer base_model:yihongLiu/furina autotrain_compatible endpoints_compatible region:us