File size: 2,379 Bytes
368f5ba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_latin_original_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_original_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: 0.0314
- Spearman Corr: 0.7391
## 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 | 1.75 | 200 | 0.0347 | 0.6054 |
| 0.0869 | 3.51 | 400 | 0.0244 | 0.7064 |
| 0.0226 | 5.26 | 600 | 0.0236 | 0.7265 |
| 0.0164 | 7.02 | 800 | 0.0271 | 0.7412 |
| 0.0132 | 8.77 | 1000 | 0.0264 | 0.7449 |
| 0.0107 | 10.53 | 1200 | 0.0300 | 0.7453 |
| 0.0087 | 12.28 | 1400 | 0.0314 | 0.7445 |
| 0.0078 | 14.04 | 1600 | 0.0252 | 0.7416 |
| 0.0078 | 15.79 | 1800 | 0.0276 | 0.7428 |
| 0.0067 | 17.54 | 2000 | 0.0312 | 0.7400 |
| 0.0061 | 19.3 | 2200 | 0.0307 | 0.7426 |
| 0.0057 | 21.05 | 2400 | 0.0318 | 0.7400 |
| 0.0053 | 22.81 | 2600 | 0.0326 | 0.7363 |
| 0.0049 | 24.56 | 2800 | 0.0314 | 0.7391 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|