metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: food101_vit_model
results: []
food101_vit_model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7311
- Accuracy: 0.8536
- Precision: 0.8531
- Recall: 0.8536
- F1: 0.8529
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.726 | 0.9994 | 1183 | 1.4984 | 0.7974 | 0.8021 | 0.7974 | 0.7906 |
| 0.9996 | 1.9996 | 2367 | 0.8596 | 0.8417 | 0.8430 | 0.8417 | 0.8413 |
| 0.8383 | 2.9981 | 3549 | 0.7311 | 0.8536 | 0.8531 | 0.8536 | 0.8529 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1