|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: distilbert-base-uncased_fold_4_ternary_v1 |
|
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_4_ternary_v1 |
|
|
|
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: 1.9355 |
|
- F1: 0.7891 |
|
|
|
## 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 | 0.5637 | 0.7485 | |
|
| 0.5729 | 2.0 | 578 | 0.5305 | 0.7805 | |
|
| 0.5729 | 3.0 | 867 | 0.6948 | 0.7670 | |
|
| 0.2548 | 4.0 | 1156 | 0.8351 | 0.7744 | |
|
| 0.2548 | 5.0 | 1445 | 1.0005 | 0.8027 | |
|
| 0.1157 | 6.0 | 1734 | 1.1578 | 0.7978 | |
|
| 0.0473 | 7.0 | 2023 | 1.2275 | 0.7953 | |
|
| 0.0473 | 8.0 | 2312 | 1.3245 | 0.7916 | |
|
| 0.0276 | 9.0 | 2601 | 1.3728 | 0.7953 | |
|
| 0.0276 | 10.0 | 2890 | 1.4577 | 0.7867 | |
|
| 0.0149 | 11.0 | 3179 | 1.5832 | 0.7731 | |
|
| 0.0149 | 12.0 | 3468 | 1.5056 | 0.7818 | |
|
| 0.0143 | 13.0 | 3757 | 1.6263 | 0.7904 | |
|
| 0.0066 | 14.0 | 4046 | 1.6596 | 0.7793 | |
|
| 0.0066 | 15.0 | 4335 | 1.6795 | 0.7941 | |
|
| 0.0022 | 16.0 | 4624 | 1.8443 | 0.7744 | |
|
| 0.0022 | 17.0 | 4913 | 1.7160 | 0.7953 | |
|
| 0.0034 | 18.0 | 5202 | 1.7819 | 0.7781 | |
|
| 0.0034 | 19.0 | 5491 | 1.7931 | 0.7904 | |
|
| 0.0036 | 20.0 | 5780 | 1.8447 | 0.7818 | |
|
| 0.0014 | 21.0 | 6069 | 1.9975 | 0.7707 | |
|
| 0.0014 | 22.0 | 6358 | 1.9324 | 0.7830 | |
|
| 0.0008 | 23.0 | 6647 | 1.9086 | 0.7842 | |
|
| 0.0008 | 24.0 | 6936 | 1.9507 | 0.7867 | |
|
| 0.0002 | 25.0 | 7225 | 1.9355 | 0.7891 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.0 |
|
- Pytorch 1.12.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
