|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: dit-small_tobacco3482_kd_CEKD_t5.0_a0.5 |
|
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. --> |
|
|
|
# dit-small_tobacco3482_kd_CEKD_t5.0_a0.5 |
|
|
|
This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.7912 |
|
- Accuracy: 0.185 |
|
- Brier Loss: 0.8688 |
|
- Nll: 5.6106 |
|
- F1 Micro: 0.185 |
|
- F1 Macro: 0.0488 |
|
- Ece: 0.2524 |
|
- Aurc: 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 256 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:| |
|
| No log | 0.96 | 3 | 4.0715 | 0.06 | 0.9043 | 8.8976 | 0.06 | 0.0114 | 0.1751 | 0.9034 | |
|
| No log | 1.96 | 6 | 3.9774 | 0.18 | 0.8893 | 8.0316 | 0.18 | 0.0305 | 0.2237 | 0.8040 | |
|
| No log | 2.96 | 9 | 3.8805 | 0.18 | 0.8782 | 8.6752 | 0.18 | 0.0305 | 0.2566 | 0.8189 | |
|
| No log | 3.96 | 12 | 3.8615 | 0.18 | 0.8836 | 8.9177 | 0.18 | 0.0305 | 0.2645 | 0.8205 | |
|
| No log | 4.96 | 15 | 3.8624 | 0.185 | 0.8844 | 6.3245 | 0.185 | 0.0488 | 0.2727 | 0.7889 | |
|
| No log | 5.96 | 18 | 3.8605 | 0.185 | 0.8813 | 5.1679 | 0.185 | 0.0488 | 0.2558 | 0.7797 | |
|
| No log | 6.96 | 21 | 3.8511 | 0.185 | 0.8774 | 5.1770 | 0.185 | 0.0488 | 0.2510 | 0.7741 | |
|
| No log | 7.96 | 24 | 3.8410 | 0.185 | 0.8751 | 5.6014 | 0.185 | 0.0488 | 0.2458 | 0.7699 | |
|
| No log | 8.96 | 27 | 3.8317 | 0.185 | 0.8733 | 5.9766 | 0.185 | 0.0488 | 0.2537 | 0.7681 | |
|
| No log | 9.96 | 30 | 3.8259 | 0.185 | 0.8724 | 6.0278 | 0.185 | 0.0488 | 0.2473 | 0.7689 | |
|
| No log | 10.96 | 33 | 3.8226 | 0.185 | 0.8724 | 6.8070 | 0.185 | 0.0488 | 0.2618 | 0.7671 | |
|
| No log | 11.96 | 36 | 3.8209 | 0.185 | 0.8730 | 7.6044 | 0.185 | 0.0488 | 0.2539 | 0.7643 | |
|
| No log | 12.96 | 39 | 3.8187 | 0.185 | 0.8730 | 8.1654 | 0.185 | 0.0488 | 0.2542 | 0.7612 | |
|
| No log | 13.96 | 42 | 3.8147 | 0.185 | 0.8725 | 7.1073 | 0.185 | 0.0488 | 0.2542 | 0.7566 | |
|
| No log | 14.96 | 45 | 3.8096 | 0.185 | 0.8720 | 6.3875 | 0.185 | 0.0488 | 0.2565 | 0.7566 | |
|
| No log | 15.96 | 48 | 3.8052 | 0.185 | 0.8712 | 6.0256 | 0.185 | 0.0488 | 0.2518 | 0.7524 | |
|
| No log | 16.96 | 51 | 3.8022 | 0.185 | 0.8707 | 5.7809 | 0.185 | 0.0488 | 0.2558 | 0.7485 | |
|
| No log | 17.96 | 54 | 3.8008 | 0.185 | 0.8701 | 5.6835 | 0.185 | 0.0488 | 0.2496 | 0.7442 | |
|
| No log | 18.96 | 57 | 3.7992 | 0.185 | 0.8700 | 5.3867 | 0.185 | 0.0488 | 0.2490 | 0.7421 | |
|
| No log | 19.96 | 60 | 3.7965 | 0.185 | 0.8694 | 5.4928 | 0.185 | 0.0488 | 0.2478 | 0.7406 | |
|
| No log | 20.96 | 63 | 3.7948 | 0.185 | 0.8693 | 5.5527 | 0.185 | 0.0488 | 0.2481 | 0.7405 | |
|
| No log | 21.96 | 66 | 3.7932 | 0.185 | 0.8691 | 5.5585 | 0.185 | 0.0488 | 0.2564 | 0.7396 | |
|
| No log | 22.96 | 69 | 3.7921 | 0.185 | 0.8689 | 5.5607 | 0.185 | 0.0488 | 0.2479 | 0.7391 | |
|
| No log | 23.96 | 72 | 3.7915 | 0.185 | 0.8688 | 5.6116 | 0.185 | 0.0488 | 0.2523 | 0.7390 | |
|
| No log | 24.96 | 75 | 3.7912 | 0.185 | 0.8688 | 5.6106 | 0.185 | 0.0488 | 0.2524 | 0.7391 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1.post200 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
