|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: distilbert-base-uncased_fold_3_ternary |
|
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. --> |
|
|
|
# distilbert-base-uncased_fold_3_ternary |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7987 |
|
- F1: 0.7460 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| No log | 1.0 | 289 | 0.5903 | 0.6893 | |
|
| 0.5417 | 2.0 | 578 | 0.5822 | 0.7130 | |
|
| 0.5417 | 3.0 | 867 | 0.6471 | 0.7385 | |
|
| 0.2298 | 4.0 | 1156 | 0.8933 | 0.7322 | |
|
| 0.2298 | 5.0 | 1445 | 1.1002 | 0.7147 | |
|
| 0.1012 | 6.0 | 1734 | 1.2041 | 0.7249 | |
|
| 0.0508 | 7.0 | 2023 | 1.3575 | 0.7195 | |
|
| 0.0508 | 8.0 | 2312 | 1.3896 | 0.7385 | |
|
| 0.018 | 9.0 | 2601 | 1.5363 | 0.7238 | |
|
| 0.018 | 10.0 | 2890 | 1.5336 | 0.7364 | |
|
| 0.0142 | 11.0 | 3179 | 1.6335 | 0.7308 | |
|
| 0.0142 | 12.0 | 3468 | 1.6915 | 0.7295 | |
|
| 0.0047 | 13.0 | 3757 | 1.7087 | 0.7427 | |
|
| 0.0058 | 14.0 | 4046 | 1.7875 | 0.7378 | |
|
| 0.0058 | 15.0 | 4335 | 1.7649 | 0.7438 | |
|
| 0.0051 | 16.0 | 4624 | 1.7987 | 0.7460 | |
|
| 0.0051 | 17.0 | 4913 | 1.8435 | 0.7404 | |
|
| 0.0025 | 18.0 | 5202 | 1.9623 | 0.7257 | |
|
| 0.0025 | 19.0 | 5491 | 1.9005 | 0.7304 | |
|
| 0.0029 | 20.0 | 5780 | 1.9437 | 0.7374 | |
|
| 0.0011 | 21.0 | 6069 | 1.9840 | 0.7268 | |
|
| 0.0011 | 22.0 | 6358 | 1.9411 | 0.7346 | |
|
| 0.0025 | 23.0 | 6647 | 1.9233 | 0.7438 | |
|
| 0.0025 | 24.0 | 6936 | 1.9415 | 0.7395 | |
|
| 0.0015 | 25.0 | 7225 | 1.9481 | 0.7411 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.0 |
|
- Pytorch 1.12.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
