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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_original_esp-kin-eng_train_spearman_corr
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_original_esp-kin-eng_train_spearman_corr
This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0243
- Spearman Corr: 0.7225
## 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 | 1.63 | 200 | 0.0285 | 0.5491 |
| 0.0764 | 3.27 | 400 | 0.0332 | 0.6502 |
| 0.0248 | 4.9 | 600 | 0.0243 | 0.6852 |
| 0.0185 | 6.53 | 800 | 0.0217 | 0.7121 |
| 0.0148 | 8.16 | 1000 | 0.0270 | 0.7180 |
| 0.0148 | 9.8 | 1200 | 0.0243 | 0.7170 |
| 0.0121 | 11.43 | 1400 | 0.0240 | 0.7203 |
| 0.01 | 13.06 | 1600 | 0.0250 | 0.7205 |
| 0.0083 | 14.69 | 1800 | 0.0251 | 0.7242 |
| 0.0073 | 16.33 | 2000 | 0.0243 | 0.7153 |
| 0.0073 | 17.96 | 2200 | 0.0257 | 0.7238 |
| 0.0064 | 19.59 | 2400 | 0.0235 | 0.7228 |
| 0.0058 | 21.22 | 2600 | 0.0246 | 0.7193 |
| 0.0054 | 22.86 | 2800 | 0.0246 | 0.7221 |
| 0.0051 | 24.49 | 3000 | 0.0235 | 0.7222 |
| 0.0048 | 26.12 | 3200 | 0.0236 | 0.7224 |
| 0.0048 | 27.76 | 3400 | 0.0243 | 0.7225 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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