metadata
library_name: transformers
base_model: microsoft/dit-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Seed_Classifier_V2
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
Seed_Classifier_V2
This model is a fine-tuned version of microsoft/dit-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.6985
- Accuracy: 0.0
- Weighted f1: 0.0
- Micro f1: 0.0
- Macro f1: 0.0
- Weighted recall: 0.0
- Micro recall: 0.0
- Macro recall: 0.0
- Weighted precision: 0.0
- Micro precision: 0.0
- Macro precision: 0.0
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 18
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.3829 | 1.0 | 1 | 1.0584 | 0.5 | 0.3333 | 0.5 | 0.3333 | 0.5 | 0.5 | 0.5 | 0.25 | 0.5 | 0.25 |
0.3829 | 2.0 | 2 | 1.2877 | 0.25 | 0.2 | 0.25 | 0.2 | 0.25 | 0.25 | 0.25 | 0.1667 | 0.25 | 0.1667 |
0.3829 | 3.0 | 3 | 2.2985 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3829 | 4.0 | 4 | 2.4998 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3829 | 5.0 | 5 | 2.2230 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3829 | 6.0 | 6 | 1.9467 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3829 | 7.0 | 7 | 1.7201 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 8.0 | 8 | 1.5736 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 9.0 | 9 | 1.5412 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 10.0 | 10 | 1.5484 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 11.0 | 11 | 1.5762 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 12.0 | 12 | 1.5907 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 13.0 | 13 | 1.6231 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 14.0 | 14 | 1.6462 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3628 | 15.0 | 15 | 1.6710 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3175 | 16.0 | 16 | 1.6883 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3175 | 17.0 | 17 | 1.6994 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.3175 | 18.0 | 18 | 1.6985 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1