|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: dit-tiny_tobacco3482_kd_CEKD_t2.5_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-tiny_tobacco3482_kd_CEKD_t2.5_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: 3.9560 |
|
- Accuracy: 0.18 |
|
- Brier Loss: 0.8800 |
|
- Nll: 6.8606 |
|
- F1 Micro: 0.18 |
|
- F1 Macro: 0.0306 |
|
- Ece: 0.2612 |
|
- Aurc: 0.8512 |
|
|
|
## 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 | 4.2281 | 0.145 | 0.8999 | 10.1620 | 0.145 | 0.0253 | 0.2222 | 0.8467 | |
|
| No log | 1.96 | 6 | 4.1872 | 0.145 | 0.8946 | 10.5915 | 0.145 | 0.0253 | 0.2275 | 0.8468 | |
|
| No log | 2.96 | 9 | 4.1248 | 0.155 | 0.8866 | 8.6280 | 0.155 | 0.0360 | 0.2179 | 0.8487 | |
|
| No log | 3.96 | 12 | 4.0716 | 0.155 | 0.8806 | 6.5480 | 0.155 | 0.0272 | 0.2254 | 0.8851 | |
|
| No log | 4.96 | 15 | 4.0359 | 0.155 | 0.8778 | 6.7781 | 0.155 | 0.0271 | 0.2310 | 0.8931 | |
|
| No log | 5.96 | 18 | 4.0135 | 0.155 | 0.8774 | 7.8547 | 0.155 | 0.0271 | 0.2345 | 0.8965 | |
|
| No log | 6.96 | 21 | 3.9978 | 0.185 | 0.8779 | 8.3528 | 0.185 | 0.0468 | 0.2615 | 0.8612 | |
|
| No log | 7.96 | 24 | 3.9867 | 0.18 | 0.8789 | 7.6001 | 0.18 | 0.0308 | 0.2618 | 0.8546 | |
|
| No log | 8.96 | 27 | 3.9782 | 0.18 | 0.8796 | 7.0871 | 0.18 | 0.0306 | 0.2613 | 0.8538 | |
|
| No log | 9.96 | 30 | 3.9726 | 0.18 | 0.8800 | 7.0519 | 0.18 | 0.0306 | 0.2687 | 0.8545 | |
|
| No log | 10.96 | 33 | 3.9684 | 0.18 | 0.8803 | 7.0277 | 0.18 | 0.0306 | 0.2656 | 0.8537 | |
|
| No log | 11.96 | 36 | 3.9654 | 0.18 | 0.8805 | 7.0162 | 0.18 | 0.0306 | 0.2708 | 0.8536 | |
|
| No log | 12.96 | 39 | 3.9633 | 0.18 | 0.8805 | 7.0056 | 0.18 | 0.0306 | 0.2619 | 0.8535 | |
|
| No log | 13.96 | 42 | 3.9614 | 0.18 | 0.8804 | 6.9981 | 0.18 | 0.0306 | 0.2617 | 0.8532 | |
|
| No log | 14.96 | 45 | 3.9598 | 0.18 | 0.8804 | 6.9923 | 0.18 | 0.0306 | 0.2669 | 0.8531 | |
|
| No log | 15.96 | 48 | 3.9586 | 0.18 | 0.8803 | 6.9334 | 0.18 | 0.0306 | 0.2669 | 0.8529 | |
|
| No log | 16.96 | 51 | 3.9578 | 0.18 | 0.8802 | 6.9237 | 0.18 | 0.0306 | 0.2716 | 0.8522 | |
|
| No log | 17.96 | 54 | 3.9576 | 0.18 | 0.8802 | 6.8704 | 0.18 | 0.0306 | 0.2666 | 0.8521 | |
|
| No log | 18.96 | 57 | 3.9574 | 0.18 | 0.8802 | 6.8662 | 0.18 | 0.0306 | 0.2664 | 0.8523 | |
|
| No log | 19.96 | 60 | 3.9568 | 0.18 | 0.8801 | 6.8641 | 0.18 | 0.0306 | 0.2614 | 0.8518 | |
|
| No log | 20.96 | 63 | 3.9566 | 0.18 | 0.8801 | 6.8634 | 0.18 | 0.0306 | 0.2659 | 0.8516 | |
|
| No log | 21.96 | 66 | 3.9563 | 0.18 | 0.8800 | 6.8632 | 0.18 | 0.0306 | 0.2612 | 0.8516 | |
|
| No log | 22.96 | 69 | 3.9561 | 0.18 | 0.8800 | 6.8620 | 0.18 | 0.0306 | 0.2612 | 0.8513 | |
|
| No log | 23.96 | 72 | 3.9561 | 0.18 | 0.8800 | 6.8611 | 0.18 | 0.0306 | 0.2612 | 0.8513 | |
|
| No log | 24.96 | 75 | 3.9560 | 0.18 | 0.8800 | 6.8606 | 0.18 | 0.0306 | 0.2612 | 0.8512 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1.post200 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
