metadata
license: apache-2.0
base_model: NekoFi/content-manage-exp2
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: portrait_cosu_exp3
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: 0.9148936170212766
- name: Precision
type: precision
value: 0.9189941972920695
- name: Recall
type: recall
value: 0.9148936170212766
- name: F1
type: f1
value: 0.9152832982620216
portrait_cosu_exp3
This model is a fine-tuned version of NekoFi/content-manage-exp2 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2524
- Accuracy: 0.9149
- Precision: 0.9190
- Recall: 0.9149
- F1: 0.9153
- Confusion Matrix: [[19, 1], [3, 24]]
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Confusion Matrix |
|---|---|---|---|---|---|---|---|---|
| No log | 0.9231 | 6 | 0.2921 | 0.8511 | 0.8527 | 0.8511 | 0.8515 | [[17, 3], [4, 23]] |
| 0.5415 | 2.0 | 13 | 0.2564 | 0.9362 | 0.9426 | 0.9362 | 0.9353 | [[17, 3], [0, 27]] |
| 0.5415 | 2.9231 | 19 | 0.3605 | 0.8723 | 0.8864 | 0.8723 | 0.8730 | [[19, 1], [5, 22]] |
| 0.378 | 3.6923 | 24 | 0.2524 | 0.9149 | 0.9190 | 0.9149 | 0.9153 | [[19, 1], [3, 24]] |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1