resnet-18-resnet-18
This model is a fine-tuned version of microsoft/resnet-18 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 5878685290980833992550249398272.0000
- Accuracy: 0.3542
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8889 | 6 | 5256596847186447919144532705280.0000 | 0.3542 |
| 6252348666680642391375611953152.0000 | 1.9259 | 13 | 5816409290772115792559022800896.0000 | 0.3542 |
| 5941338476045271956843984322560.0000 | 2.9630 | 20 | 5569209952566045840858865991680.0000 | 0.3542 |
| 5941338476045271956843984322560.0000 | 4.0 | 27 | 5764530657074993210784856670208.0000 | 0.3542 |
| 5978113032337293509815187800064.0000 | 4.8889 | 33 | 5717174614869048956753266343936.0000 | 0.3542 |
| 6377920275134342219963975073792.0000 | 5.9259 | 40 | 5885479454087068208512098107392.0000 | 0.3542 |
| 6377920275134342219963975073792.0000 | 6.9630 | 47 | 5693683372805207289944963284992.0000 | 0.3542 |
| 6201930657158778429750307192832.0000 | 8.0 | 54 | 5815479022353922335409086398464.0000 | 0.3542 |
| 6266525497982100125501481811968.0000 | 8.8889 | 60 | 5878685290980833992550249398272.0000 | 0.3542 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
microsoft/resnet-18