File size: 2,134 Bytes
187e553 2bf71ba 187e553 2bf71ba 187e553 2bf71ba 187e553 2bf71ba 187e553 2bf71ba 187e553 |
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 |
---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 0.50-200Train-100Test-swinv2-base
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. -->
# 0.50-200Train-100Test-swinv2-base
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8692
- Accuracy: 0.8218
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.4079 | 0.9931 | 36 | 0.8584 | 0.7266 |
| 0.4802 | 1.9862 | 72 | 0.6626 | 0.7886 |
| 0.218 | 2.9793 | 108 | 0.7199 | 0.7904 |
| 0.1184 | 4.0 | 145 | 0.7587 | 0.8096 |
| 0.0531 | 4.9931 | 181 | 0.7530 | 0.8157 |
| 0.0579 | 5.9862 | 217 | 0.7707 | 0.8070 |
| 0.031 | 6.9793 | 253 | 0.8554 | 0.8262 |
| 0.0094 | 8.0 | 290 | 0.8697 | 0.8122 |
| 0.0131 | 8.9931 | 326 | 0.8843 | 0.8227 |
| 0.0128 | 9.9310 | 360 | 0.8692 | 0.8218 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
|