metadata
license: apache-2.0
base_model: facebook/convnext-large-224-22k-1k
tags:
- generated_from_trainer
datasets:
- imagenet_10
metrics:
- accuracy
model-index:
- name: image_classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagenet_10
type: imagenet_10
config: default
split: train[:7000]
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9942857142857143
image_classification
This model is a fine-tuned version of facebook/convnext-large-224-22k-1k on the imagenet_10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0357
- Accuracy: 0.9943
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: 0.0001
- train_batch_size: 17
- eval_batch_size: 17
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 330 | 0.0637 | 0.9843 |
| 0.0602 | 2.0 | 660 | 0.0664 | 0.9821 |
| 0.0602 | 3.0 | 990 | 0.0843 | 0.9843 |
| 0.0468 | 4.0 | 1320 | 0.0452 | 0.9879 |
| 0.0313 | 5.0 | 1650 | 0.0347 | 0.9914 |
| 0.0313 | 6.0 | 1980 | 0.0432 | 0.9914 |
| 0.0232 | 7.0 | 2310 | 0.0314 | 0.99 |
| 0.0223 | 8.0 | 2640 | 0.0337 | 0.9921 |
| 0.0223 | 9.0 | 2970 | 0.0381 | 0.99 |
| 0.0177 | 10.0 | 3300 | 0.0321 | 0.9921 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3