File size: 2,421 Bytes
f9b9ba0 dde12b2 f9b9ba0 dde12b2 f9b9ba0 dde12b2 f9b9ba0 |
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 |
---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window16-256
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SwinV2-Base-Document-Classifier
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. -->
# SwinV2-Base-Document-Classifier
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co./microsoft/swinv2-base-patch4-window16-256) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0191
- Accuracy: 0.9946
- F1: 0.9946
- Precision: 0.9946
- Recall: 0.9946
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 800
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0794 | 0.2 | 160 | 0.0330 | 0.9899 | 0.9899 | 0.9899 | 0.9899 |
| 0.0619 | 0.3 | 240 | 0.0278 | 0.9908 | 0.9908 | 0.9908 | 0.9909 |
| 0.0499 | 0.4 | 320 | 0.0272 | 0.9914 | 0.9914 | 0.9914 | 0.9914 |
| 0.0482 | 0.5 | 400 | 0.0275 | 0.9917 | 0.9917 | 0.9917 | 0.9917 |
| 0.0416 | 1.1 | 480 | 0.0218 | 0.9931 | 0.9931 | 0.9931 | 0.9931 |
| 0.0353 | 1.2 | 560 | 0.0208 | 0.9942 | 0.9942 | 0.9942 | 0.9942 |
| 0.0306 | 1.3 | 640 | 0.0183 | 0.9949 | 0.9949 | 0.9949 | 0.9949 |
| 0.0296 | 1.4 | 720 | 0.0198 | 0.9944 | 0.9944 | 0.9944 | 0.9944 |
| 0.0305 | 1.5 | 800 | 0.0191 | 0.9946 | 0.9946 | 0.9946 | 0.9946 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2
|