update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
model-index:
|
| 8 |
+
- name: vit-base_rvl-cdip
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# vit-base_rvl-cdip
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 0.5535
|
| 20 |
+
- Accuracy: 0.897
|
| 21 |
+
- Brier Loss: 0.1768
|
| 22 |
+
- Nll: 1.0978
|
| 23 |
+
- F1 Micro: 0.897
|
| 24 |
+
- F1 Macro: 0.8972
|
| 25 |
+
- Ece: 0.0801
|
| 26 |
+
- Aurc: 0.0180
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 2e-05
|
| 46 |
+
- train_batch_size: 4
|
| 47 |
+
- eval_batch_size: 4
|
| 48 |
+
- seed: 42
|
| 49 |
+
- gradient_accumulation_steps: 16
|
| 50 |
+
- total_train_batch_size: 64
|
| 51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 52 |
+
- lr_scheduler_type: linear
|
| 53 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 54 |
+
- num_epochs: 10
|
| 55 |
+
|
| 56 |
+
### Training results
|
| 57 |
+
|
| 58 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
|
| 59 |
+
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
|
| 60 |
+
| 0.676 | 1.0 | 5000 | 0.6451 | 0.8230 | 0.2574 | 1.2627 | 0.8230 | 0.8237 | 0.0458 | 0.0425 |
|
| 61 |
+
| 0.4207 | 2.0 | 10000 | 0.4251 | 0.8766 | 0.1800 | 1.2821 | 0.8766 | 0.8779 | 0.0154 | 0.0218 |
|
| 62 |
+
| 0.3335 | 3.0 | 15000 | 0.3914 | 0.8861 | 0.1676 | 1.2589 | 0.8861 | 0.8858 | 0.0252 | 0.0192 |
|
| 63 |
+
| 0.2447 | 4.0 | 20000 | 0.3687 | 0.8934 | 0.1574 | 1.2243 | 0.8934 | 0.8937 | 0.0331 | 0.0164 |
|
| 64 |
+
| 0.1623 | 5.0 | 25000 | 0.3843 | 0.8976 | 0.1583 | 1.1553 | 0.8976 | 0.8973 | 0.0461 | 0.0159 |
|
| 65 |
+
| 0.1083 | 6.0 | 30000 | 0.4131 | 0.8964 | 0.1624 | 1.1514 | 0.8964 | 0.8967 | 0.0581 | 0.0163 |
|
| 66 |
+
| 0.0652 | 7.0 | 35000 | 0.4633 | 0.8966 | 0.1690 | 1.1300 | 0.8966 | 0.8967 | 0.0692 | 0.0169 |
|
| 67 |
+
| 0.0361 | 8.0 | 40000 | 0.5068 | 0.8976 | 0.1723 | 1.1161 | 0.8976 | 0.8976 | 0.0737 | 0.0175 |
|
| 68 |
+
| 0.0192 | 9.0 | 45000 | 0.5418 | 0.8982 | 0.1748 | 1.1015 | 0.8982 | 0.8983 | 0.0779 | 0.0179 |
|
| 69 |
+
| 0.0111 | 10.0 | 50000 | 0.5535 | 0.897 | 0.1768 | 1.0978 | 0.897 | 0.8972 | 0.0801 | 0.0180 |
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
### Framework versions
|
| 73 |
+
|
| 74 |
+
- Transformers 4.26.1
|
| 75 |
+
- Pytorch 1.13.1.post200
|
| 76 |
+
- Datasets 2.9.0
|
| 77 |
+
- Tokenizers 0.13.2
|