metadata

library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swinv2-tiny-patch4-window8-256-Ocular-Toxoplasmosis-DA
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8548387096774194

swinv2-tiny-patch4-window8-256-Ocular-Toxoplasmosis-DA

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.5075
Accuracy: 0.8548

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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3402	0.9630	13	1.1682	0.5484
1.1725	2.0	27	1.0025	0.6290
0.8824	2.9630	40	0.7644	0.6613
0.7342	4.0	54	0.5840	0.7258
0.6734	4.9630	67	0.6754	0.6452
0.5167	6.0	81	0.5904	0.6935
0.5009	6.9630	94	0.5549	0.6935
0.4988	8.0	108	0.6204	0.6774
0.3856	8.9630	121	0.4463	0.8226
0.4057	10.0	135	0.5232	0.7903
0.3929	10.9630	148	0.4580	0.8387
0.3638	12.0	162	0.5115	0.7742
0.3248	12.9630	175	0.5313	0.7742
0.2673	14.0	189	0.5203	0.7903
0.2922	14.9630	202	0.4315	0.8387
0.2803	16.0	216	0.4577	0.8387
0.2735	16.9630	229	0.5467	0.8065
0.2586	18.0	243	0.5236	0.8387
0.2366	18.9630	256	0.5075	0.8548
0.2347	20.0	270	0.5179	0.8387
0.2046	20.9630	283	0.5428	0.8387
0.2289	22.0	297	0.5748	0.8387
0.2195	22.9630	310	0.5969	0.8226
0.2224	24.0	324	0.6092	0.8226
0.2167	24.9630	337	0.6333	0.8226
0.1956	26.0	351	0.5993	0.8226
0.2174	26.9630	364	0.6063	0.8548
0.1999	28.0	378	0.6414	0.8387
0.1667	28.9630	391	0.6297	0.8387
0.1835	30.0	405	0.6149	0.8226
0.186	30.9630	418	0.6430	0.8387
0.1749	32.0	432	0.6678	0.8387
0.1663	32.9630	445	0.6829	0.8387
0.1557	34.0	459	0.6557	0.8387
0.1913	34.9630	472	0.6275	0.8387
0.1775	36.0	486	0.6555	0.8548
0.152	36.9630	499	0.6653	0.8548
0.1897	38.0	513	0.6682	0.8548
0.1589	38.5185	520	0.6679	0.8548

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1