update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,91 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
metrics:
|
| 5 |
+
- accuracy
|
| 6 |
+
model-index:
|
| 7 |
+
- name: dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.9
|
| 8 |
+
results: []
|
| 9 |
+
---
|
| 10 |
+
|
| 11 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 12 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 13 |
+
|
| 14 |
+
# dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.9
|
| 15 |
+
|
| 16 |
+
This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the None dataset.
|
| 17 |
+
It achieves the following results on the evaluation set:
|
| 18 |
+
- Loss: 2.5379
|
| 19 |
+
- Accuracy: 0.18
|
| 20 |
+
- Brier Loss: 0.8746
|
| 21 |
+
- Nll: 6.7389
|
| 22 |
+
- F1 Micro: 0.18
|
| 23 |
+
- F1 Macro: 0.0306
|
| 24 |
+
- Ece: 0.2460
|
| 25 |
+
- Aurc: 0.8496
|
| 26 |
+
|
| 27 |
+
## Model description
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Intended uses & limitations
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training and evaluation data
|
| 36 |
+
|
| 37 |
+
More information needed
|
| 38 |
+
|
| 39 |
+
## Training procedure
|
| 40 |
+
|
| 41 |
+
### Training hyperparameters
|
| 42 |
+
|
| 43 |
+
The following hyperparameters were used during training:
|
| 44 |
+
- learning_rate: 2e-05
|
| 45 |
+
- train_batch_size: 16
|
| 46 |
+
- eval_batch_size: 16
|
| 47 |
+
- seed: 42
|
| 48 |
+
- gradient_accumulation_steps: 16
|
| 49 |
+
- total_train_batch_size: 256
|
| 50 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 51 |
+
- lr_scheduler_type: linear
|
| 52 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 53 |
+
- num_epochs: 25
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:-------:|:--------:|:--------:|:------:|:------:|
|
| 59 |
+
| No log | 0.96 | 3 | 2.6891 | 0.145 | 0.8999 | 10.1550 | 0.145 | 0.0253 | 0.2220 | 0.8466 |
|
| 60 |
+
| No log | 1.96 | 6 | 2.6592 | 0.145 | 0.8947 | 10.5706 | 0.145 | 0.0253 | 0.2238 | 0.8463 |
|
| 61 |
+
| No log | 2.96 | 9 | 2.6158 | 0.14 | 0.8869 | 8.5528 | 0.14 | 0.0422 | 0.2066 | 0.8175 |
|
| 62 |
+
| No log | 3.96 | 12 | 2.5827 | 0.175 | 0.8810 | 6.5464 | 0.175 | 0.0467 | 0.2385 | 0.8661 |
|
| 63 |
+
| No log | 4.96 | 15 | 2.5647 | 0.155 | 0.8781 | 6.8570 | 0.155 | 0.0274 | 0.2316 | 0.8886 |
|
| 64 |
+
| No log | 5.96 | 18 | 2.5566 | 0.19 | 0.8772 | 8.4283 | 0.19 | 0.0413 | 0.2460 | 0.8532 |
|
| 65 |
+
| No log | 6.96 | 21 | 2.5515 | 0.18 | 0.8769 | 7.6865 | 0.18 | 0.0308 | 0.2480 | 0.8517 |
|
| 66 |
+
| No log | 7.96 | 24 | 2.5475 | 0.18 | 0.8767 | 6.9727 | 0.18 | 0.0306 | 0.2469 | 0.8521 |
|
| 67 |
+
| No log | 8.96 | 27 | 2.5438 | 0.18 | 0.8762 | 6.9080 | 0.18 | 0.0306 | 0.2438 | 0.8525 |
|
| 68 |
+
| No log | 9.96 | 30 | 2.5420 | 0.18 | 0.8758 | 6.8906 | 0.18 | 0.0306 | 0.2521 | 0.8528 |
|
| 69 |
+
| No log | 10.96 | 33 | 2.5410 | 0.18 | 0.8755 | 6.8317 | 0.18 | 0.0306 | 0.2516 | 0.8524 |
|
| 70 |
+
| No log | 11.96 | 36 | 2.5404 | 0.18 | 0.8753 | 6.7606 | 0.18 | 0.0306 | 0.2469 | 0.8516 |
|
| 71 |
+
| No log | 12.96 | 39 | 2.5401 | 0.18 | 0.8752 | 6.7444 | 0.18 | 0.0306 | 0.2425 | 0.8516 |
|
| 72 |
+
| No log | 13.96 | 42 | 2.5397 | 0.18 | 0.8751 | 6.7397 | 0.18 | 0.0306 | 0.2498 | 0.8514 |
|
| 73 |
+
| No log | 14.96 | 45 | 2.5393 | 0.18 | 0.8750 | 6.7390 | 0.18 | 0.0306 | 0.2579 | 0.8511 |
|
| 74 |
+
| No log | 15.96 | 48 | 2.5389 | 0.18 | 0.8749 | 6.7366 | 0.18 | 0.0306 | 0.2463 | 0.8513 |
|
| 75 |
+
| No log | 16.96 | 51 | 2.5387 | 0.18 | 0.8749 | 6.7390 | 0.18 | 0.0306 | 0.2465 | 0.8510 |
|
| 76 |
+
| No log | 17.96 | 54 | 2.5389 | 0.18 | 0.8749 | 6.7382 | 0.18 | 0.0306 | 0.2425 | 0.8505 |
|
| 77 |
+
| No log | 18.96 | 57 | 2.5389 | 0.18 | 0.8749 | 6.7397 | 0.18 | 0.0306 | 0.2463 | 0.8504 |
|
| 78 |
+
| No log | 19.96 | 60 | 2.5384 | 0.18 | 0.8748 | 6.7391 | 0.18 | 0.0306 | 0.2421 | 0.8495 |
|
| 79 |
+
| No log | 20.96 | 63 | 2.5383 | 0.18 | 0.8747 | 6.7396 | 0.18 | 0.0306 | 0.2422 | 0.8500 |
|
| 80 |
+
| No log | 21.96 | 66 | 2.5380 | 0.18 | 0.8747 | 6.7399 | 0.18 | 0.0306 | 0.2460 | 0.8496 |
|
| 81 |
+
| No log | 22.96 | 69 | 2.5379 | 0.18 | 0.8746 | 6.7395 | 0.18 | 0.0306 | 0.2460 | 0.8497 |
|
| 82 |
+
| No log | 23.96 | 72 | 2.5379 | 0.18 | 0.8746 | 6.7393 | 0.18 | 0.0306 | 0.2460 | 0.8497 |
|
| 83 |
+
| No log | 24.96 | 75 | 2.5379 | 0.18 | 0.8746 | 6.7389 | 0.18 | 0.0306 | 0.2460 | 0.8496 |
|
| 84 |
+
|
| 85 |
+
|
| 86 |
+
### Framework versions
|
| 87 |
+
|
| 88 |
+
- Transformers 4.26.1
|
| 89 |
+
- Pytorch 1.13.1.post200
|
| 90 |
+
- Datasets 2.9.0
|
| 91 |
+
- Tokenizers 0.13.2
|