File size: 1,917 Bytes
e22b990 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fashion_mnist
metrics:
- accuracy
model-index:
- name: my_awesome_fashion_model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: fashion_mnist
type: fashion_mnist
config: fashion_mnist
split: train[:5000]
args: fashion_mnist
metrics:
- name: Accuracy
type: accuracy
value: 0.796
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_fashion_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fashion_mnist dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8182
- Accuracy: 0.796
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3152 | 0.99 | 62 | 1.2059 | 0.75 |
| 0.9175 | 2.0 | 125 | 0.8880 | 0.784 |
| 0.8417 | 2.98 | 186 | 0.8182 | 0.796 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
|