File size: 2,507 Bytes
93869ef |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: quickdraw-DeiT-tiny-c
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. -->
# quickdraw-DeiT-tiny-c
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9628
- Accuracy: 0.7773
## 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: 0.0008
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10000
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.315 | 0.5688 | 5000 | 1.2585 | 0.6844 |
| 1.1484 | 1.1377 | 10000 | 1.1506 | 0.7091 |
| 1.0423 | 1.7065 | 15000 | 1.0410 | 0.7327 |
| 0.9596 | 2.2753 | 20000 | 0.9754 | 0.7498 |
| 0.9363 | 2.8441 | 25000 | 0.9489 | 0.7557 |
| 0.8768 | 3.4130 | 30000 | 0.9197 | 0.7633 |
| 0.8655 | 3.9818 | 35000 | 0.8970 | 0.7688 |
| 0.815 | 4.5506 | 40000 | 0.8845 | 0.7724 |
| 0.748 | 5.1195 | 45000 | 0.8729 | 0.7761 |
| 0.7522 | 5.6883 | 50000 | 0.8562 | 0.78 |
| 0.6854 | 6.2571 | 55000 | 0.8654 | 0.7805 |
| 0.6899 | 6.8259 | 60000 | 0.8529 | 0.7838 |
| 0.6162 | 7.3948 | 65000 | 0.8787 | 0.7821 |
| 0.6159 | 7.9636 | 70000 | 0.8742 | 0.7837 |
| 0.5498 | 8.5324 | 75000 | 0.9197 | 0.7801 |
| 0.5087 | 9.1013 | 80000 | 0.9529 | 0.7782 |
| 0.5053 | 9.6701 | 85000 | 0.9628 | 0.7773 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1
|