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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_esp_kin
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_esp_kin
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: 0.8588
## 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 | 0.6 | 200 | 0.0342 | 0.6070 |
| No log | 1.21 | 400 | 0.0245 | 0.6934 |
| No log | 1.81 | 600 | 0.0230 | 0.7199 |
| 0.0458 | 2.42 | 800 | 0.0215 | 0.7448 |
| 0.0458 | 3.02 | 1000 | 0.0203 | 0.7510 |
| 0.0458 | 3.63 | 1200 | 0.0198 | 0.7712 |
| 0.02 | 4.23 | 1400 | 0.0180 | 0.7809 |
| 0.02 | 4.83 | 1600 | 0.0191 | 0.7812 |
| 0.02 | 5.44 | 1800 | 0.0182 | 0.7921 |
| 0.0142 | 6.04 | 2000 | 0.0177 | 0.8010 |
| 0.0142 | 6.65 | 2200 | 0.0170 | 0.8004 |
| 0.0142 | 7.25 | 2400 | 0.0159 | 0.8085 |
| 0.0142 | 7.85 | 2600 | 0.0161 | 0.8114 |
| 0.01 | 8.46 | 2800 | 0.0160 | 0.8142 |
| 0.01 | 9.06 | 3000 | 0.0152 | 0.8218 |
| 0.01 | 9.67 | 3200 | 0.0157 | 0.8234 |
| 0.0072 | 10.27 | 3400 | 0.0145 | 0.8303 |
| 0.0072 | 10.88 | 3600 | 0.0153 | 0.8311 |
| 0.0072 | 11.48 | 3800 | 0.0147 | 0.8311 |
| 0.0059 | 12.08 | 4000 | 0.0140 | 0.8373 |
| 0.0059 | 12.69 | 4200 | 0.0139 | 0.8401 |
| 0.0059 | 13.29 | 4400 | 0.0143 | 0.8406 |
| 0.0059 | 13.9 | 4600 | 0.0136 | 0.8447 |
| 0.0049 | 14.5 | 4800 | 0.0140 | 0.8453 |
| 0.0049 | 15.11 | 5000 | 0.0133 | 0.8452 |
| 0.0049 | 15.71 | 5200 | 0.0140 | 0.8450 |
| 0.0041 | 16.31 | 5400 | 0.0135 | 0.8481 |
| 0.0041 | 16.92 | 5600 | 0.0147 | 0.8489 |
| 0.0041 | 17.52 | 5800 | 0.0135 | 0.8492 |
| 0.0037 | 18.13 | 6000 | 0.0134 | 0.8498 |
| 0.0037 | 18.73 | 6200 | 0.0131 | 0.8492 |
| 0.0037 | 19.34 | 6400 | 0.0134 | 0.8524 |
| 0.0037 | 19.94 | 6600 | 0.0134 | 0.8536 |
| 0.0034 | 20.54 | 6800 | 0.0128 | 0.8540 |
| 0.0034 | 21.15 | 7000 | 0.0134 | 0.8539 |
| 0.0034 | 21.75 | 7200 | 0.0138 | 0.8531 |
| 0.0031 | 22.36 | 7400 | 0.0125 | 0.8562 |
| 0.0031 | 22.96 | 7600 | 0.0135 | 0.8585 |
| 0.0031 | 23.56 | 7800 | 0.0132 | 0.8569 |
| 0.0028 | 24.17 | 8000 | 0.0126 | 0.8564 |
| 0.0028 | 24.77 | 8200 | 0.0130 | 0.8574 |
| 0.0028 | 25.38 | 8400 | 0.0128 | 0.8587 |
| 0.0026 | 25.98 | 8600 | 0.0128 | 0.8595 |
| 0.0026 | 26.59 | 8800 | 0.0131 | 0.8582 |
| 0.0026 | 27.19 | 9000 | 0.0131 | 0.8588 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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