Edit model card

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
Downloads last month
4
Safetensors
Model size
86M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for NekoFi/portrait_cosu_exp3

Finetuned
(1)
this model
Finetunes
1 model

Evaluation results