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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_latin_kin-amh-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_latin_kin-amh-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: 0.0287
- Spearman Corr: 0.7455
## 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 | 0.0534 | 0.5665 |
| No log | 1.17 | 400 | 0.0303 | 0.6812 |
| No log | 1.76 | 600 | 0.0374 | 0.6929 |
| 0.0479 | 2.35 | 800 | 0.0244 | 0.7282 |
| 0.0479 | 2.93 | 1000 | 0.0333 | 0.7172 |
| 0.0479 | 3.52 | 1200 | 0.0287 | 0.7167 |
| 0.0233 | 4.11 | 1400 | 0.0287 | 0.7330 |
| 0.0233 | 4.69 | 1600 | 0.0297 | 0.7176 |
| 0.0233 | 5.28 | 1800 | 0.0255 | 0.7429 |
| 0.0233 | 5.87 | 2000 | 0.0320 | 0.7385 |
| 0.0165 | 6.45 | 2200 | 0.0273 | 0.7325 |
| 0.0165 | 7.04 | 2400 | 0.0262 | 0.7489 |
| 0.0165 | 7.62 | 2600 | 0.0343 | 0.7388 |
| 0.0121 | 8.21 | 2800 | 0.0258 | 0.7398 |
| 0.0121 | 8.8 | 3000 | 0.0298 | 0.7398 |
| 0.0121 | 9.38 | 3200 | 0.0303 | 0.7370 |
| 0.0121 | 9.97 | 3400 | 0.0316 | 0.7394 |
| 0.0095 | 10.56 | 3600 | 0.0295 | 0.7395 |
| 0.0095 | 11.14 | 3800 | 0.0299 | 0.7399 |
| 0.0095 | 11.73 | 4000 | 0.0287 | 0.7455 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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