|
|
--- |
|
|
library_name: transformers |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: eo_train1-10_eval1-10_lr1e-5 |
|
|
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. --> |
|
|
|
|
|
# eo_train1-10_eval1-10_lr1e-5 |
|
|
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4512 |
|
|
- Accuracy: 0.75 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 128 |
|
|
- eval_batch_size: 128 |
|
|
- seed: 7658372 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- training_steps: 3000 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
|
| No log | 0 | 0 | 3.0162 | 0.0 | |
|
|
| 1.4977 | 100.0 | 100 | 1.4741 | 0.5 | |
|
|
| 0.7396 | 200.0 | 200 | 0.7389 | 0.5 | |
|
|
| 0.6815 | 300.0 | 300 | 0.6810 | 0.6 | |
|
|
| 0.6378 | 400.0 | 400 | 0.6373 | 0.55 | |
|
|
| 0.5971 | 500.0 | 500 | 0.5969 | 0.6 | |
|
|
| 0.5768 | 600.0 | 600 | 0.5763 | 0.6 | |
|
|
| 0.555 | 700.0 | 700 | 0.5545 | 0.65 | |
|
|
| 0.5395 | 800.0 | 800 | 0.5393 | 0.7 | |
|
|
| 0.5279 | 900.0 | 900 | 0.5281 | 0.65 | |
|
|
| 0.5228 | 1000.0 | 1000 | 0.5224 | 0.7 | |
|
|
| 0.5161 | 1100.0 | 1100 | 0.5167 | 0.8 | |
|
|
| 0.5104 | 1200.0 | 1200 | 0.5106 | 0.8 | |
|
|
| 0.5049 | 1300.0 | 1300 | 0.5047 | 0.8 | |
|
|
| 0.4987 | 1400.0 | 1400 | 0.4991 | 0.75 | |
|
|
| 0.493 | 1500.0 | 1500 | 0.4933 | 0.7 | |
|
|
| 0.4877 | 1600.0 | 1600 | 0.4884 | 0.75 | |
|
|
| 0.4826 | 1700.0 | 1700 | 0.4824 | 0.7 | |
|
|
| 0.4766 | 1800.0 | 1800 | 0.4763 | 0.7 | |
|
|
| 0.4714 | 1900.0 | 1900 | 0.4713 | 0.7 | |
|
|
| 0.4673 | 2000.0 | 2000 | 0.4674 | 0.7 | |
|
|
| 0.4635 | 2100.0 | 2100 | 0.4633 | 0.7 | |
|
|
| 0.4602 | 2200.0 | 2200 | 0.4601 | 0.7 | |
|
|
| 0.4577 | 2300.0 | 2300 | 0.4577 | 0.75 | |
|
|
| 0.4556 | 2400.0 | 2400 | 0.4555 | 0.75 | |
|
|
| 0.4538 | 2500.0 | 2500 | 0.4538 | 0.75 | |
|
|
| 0.4525 | 2600.0 | 2600 | 0.4525 | 0.75 | |
|
|
| 0.4518 | 2700.0 | 2700 | 0.4518 | 0.75 | |
|
|
| 0.4514 | 2800.0 | 2800 | 0.4514 | 0.75 | |
|
|
| 0.4512 | 2900.0 | 2900 | 0.4512 | 0.75 | |
|
|
| 0.4512 | 3000.0 | 3000 | 0.4512 | 0.75 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.46.0 |
|
|
- Pytorch 2.5.1 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.20.1 |
|
|
|
