metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-student_kaggle
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: 0.1949685534591195
resnet-50-finetuned-student_kaggle
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 2966756414651073587838976.0000
- Accuracy: 0.1950
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2231665653697395759775744.0000 | 1.0 | 47 | 2703493994833503873662976.0000 | 0.1950 |
| 2448978214010634004070400.0000 | 2.0 | 94 | 2805605946653523096633344.0000 | 0.1950 |
| 2364532939574307232677888.0000 | 3.0 | 141 | 2845180265529529270796288.0000 | 0.1950 |
| 2331862372313962142236672.0000 | 4.0 | 188 | 3271042952136692586250240.0000 | 0.1950 |
| 2584276319587858445762560.0000 | 5.0 | 235 | 2966756414651073587838976.0000 | 0.1950 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1