File size: 2,343 Bytes
7dbfa9b a698090 7dbfa9b fdbfe13 a698090 7dbfa9b a698090 7dbfa9b a698090 7dbfa9b |
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 80 81 82 83 84 85 86 87 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-drfx-surgery-classifier
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.875
---
<!-- 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. -->
# convnext-tiny-224-drfx-surgery-classifier
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6160
- Accuracy: 0.875
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 4 | 0.7140 | 0.375 |
| No log | 2.0 | 8 | 0.6876 | 0.5 |
| 0.7104 | 3.0 | 12 | 0.6666 | 0.625 |
| 0.7104 | 4.0 | 16 | 0.6495 | 0.6875 |
| 0.6567 | 5.0 | 20 | 0.6360 | 0.75 |
| 0.6567 | 6.0 | 24 | 0.6247 | 0.8125 |
| 0.6567 | 7.0 | 28 | 0.6160 | 0.875 |
| 0.6277 | 8.0 | 32 | 0.6098 | 0.875 |
| 0.6277 | 9.0 | 36 | 0.6058 | 0.875 |
| 0.6122 | 10.0 | 40 | 0.6043 | 0.875 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|