|
---
|
|
library_name: transformers
|
|
license: apache-2.0
|
|
base_model: google/vit-base-patch16-224-in21k
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagefolder
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: emotion_classifier
|
|
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: 0.4125
|
|
---
|
|
|
|
<!-- 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. -->
|
|
|
|
# emotion_classifier
|
|
|
|
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 imagefolder dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 1.6092
|
|
- Accuracy: 0.4125
|
|
|
|
## 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: 2e-05
|
|
- train_batch_size: 16
|
|
- eval_batch_size: 16
|
|
- seed: 42
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
|
- lr_scheduler_type: linear
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
- num_epochs: 10
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| No log | 1.0 | 40 | 2.0750 | 0.15 |
|
|
| No log | 2.0 | 80 | 2.0046 | 0.1875 |
|
|
| No log | 3.0 | 120 | 1.8909 | 0.3063 |
|
|
| No log | 4.0 | 160 | 1.7726 | 0.3563 |
|
|
| No log | 5.0 | 200 | 1.6970 | 0.3438 |
|
|
| No log | 6.0 | 240 | 1.6562 | 0.3937 |
|
|
| No log | 7.0 | 280 | 1.6269 | 0.4062 |
|
|
| No log | 8.0 | 320 | 1.6092 | 0.4125 |
|
|
| No log | 9.0 | 360 | 1.6012 | 0.4125 |
|
|
| No log | 10.0 | 400 | 1.5955 | 0.4125 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.49.0
|
|
- Pytorch 2.5.1+cpu
|
|
- Datasets 3.2.0
|
|
- Tokenizers 0.21.0
|
|
|
