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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_amh_esp
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# furina_seed42_eng_amh_esp
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: 0.0131
- Spearman Corr: 0.8481
## 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 | 0.59 | 200 | 0.0247 | 0.6933 |
| No log | 1.18 | 400 | 0.0227 | 0.7395 |
| No log | 1.76 | 600 | 0.0217 | 0.7604 |
| 0.0471 | 2.35 | 800 | 0.0192 | 0.7685 |
| 0.0471 | 2.94 | 1000 | 0.0186 | 0.7805 |
| 0.0471 | 3.53 | 1200 | 0.0178 | 0.7884 |
| 0.0196 | 4.12 | 1400 | 0.0179 | 0.7961 |
| 0.0196 | 4.71 | 1600 | 0.0177 | 0.7990 |
| 0.0196 | 5.29 | 1800 | 0.0178 | 0.8035 |
| 0.0196 | 5.88 | 2000 | 0.0164 | 0.8057 |
| 0.0145 | 6.47 | 2200 | 0.0167 | 0.8070 |
| 0.0145 | 7.06 | 2400 | 0.0159 | 0.8110 |
| 0.0145 | 7.65 | 2600 | 0.0165 | 0.8121 |
| 0.0106 | 8.24 | 2800 | 0.0161 | 0.8110 |
| 0.0106 | 8.82 | 3000 | 0.0159 | 0.8148 |
| 0.0106 | 9.41 | 3200 | 0.0155 | 0.8195 |
| 0.008 | 10.0 | 3400 | 0.0151 | 0.8227 |
| 0.008 | 10.59 | 3600 | 0.0149 | 0.8253 |
| 0.008 | 11.18 | 3800 | 0.0154 | 0.8244 |
| 0.008 | 11.76 | 4000 | 0.0147 | 0.8251 |
| 0.0064 | 12.35 | 4200 | 0.0148 | 0.8249 |
| 0.0064 | 12.94 | 4400 | 0.0149 | 0.8287 |
| 0.0064 | 13.53 | 4600 | 0.0147 | 0.8297 |
| 0.0052 | 14.12 | 4800 | 0.0142 | 0.8347 |
| 0.0052 | 14.71 | 5000 | 0.0148 | 0.8314 |
| 0.0052 | 15.29 | 5200 | 0.0141 | 0.8341 |
| 0.0052 | 15.88 | 5400 | 0.0139 | 0.8386 |
| 0.0045 | 16.47 | 5600 | 0.0139 | 0.8350 |
| 0.0045 | 17.06 | 5800 | 0.0137 | 0.8389 |
| 0.0045 | 17.65 | 6000 | 0.0136 | 0.8402 |
| 0.004 | 18.24 | 6200 | 0.0139 | 0.8400 |
| 0.004 | 18.82 | 6400 | 0.0138 | 0.8414 |
| 0.004 | 19.41 | 6600 | 0.0136 | 0.8433 |
| 0.0036 | 20.0 | 6800 | 0.0140 | 0.8420 |
| 0.0036 | 20.59 | 7000 | 0.0136 | 0.8434 |
| 0.0036 | 21.18 | 7200 | 0.0137 | 0.8451 |
| 0.0036 | 21.76 | 7400 | 0.0133 | 0.8445 |
| 0.0032 | 22.35 | 7600 | 0.0135 | 0.8451 |
| 0.0032 | 22.94 | 7800 | 0.0136 | 0.8447 |
| 0.0032 | 23.53 | 8000 | 0.0136 | 0.8449 |
| 0.003 | 24.12 | 8200 | 0.0132 | 0.8463 |
| 0.003 | 24.71 | 8400 | 0.0131 | 0.8472 |
| 0.003 | 25.29 | 8600 | 0.0133 | 0.8477 |
| 0.003 | 25.88 | 8800 | 0.0135 | 0.8472 |
| 0.0028 | 26.47 | 9000 | 0.0134 | 0.8478 |
| 0.0028 | 27.06 | 9200 | 0.0131 | 0.8477 |
| 0.0028 | 27.65 | 9400 | 0.0131 | 0.8478 |
| 0.0026 | 28.24 | 9600 | 0.0130 | 0.8482 |
| 0.0026 | 28.82 | 9800 | 0.0131 | 0.8479 |
| 0.0026 | 29.41 | 10000 | 0.0131 | 0.8481 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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