|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: emotion-classification |
|
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: 0.875 |
|
--- |
|
|
|
<!-- 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-classification |
|
|
|
This model was trained from scratch on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8208 |
|
- Accuracy: 0.875 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- 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 |
|
|
|
 |
|
|
|
KeyboardInterrupt: because full disk, continue from checkpoint 270 / from epoch 54 |
|
checkpoint = "C:\Users\willi\Documents\MachineLearning_Collab\model\emotion-classification\checkpoint-270" |
|
|
|
|
|
 |
|
|
|
| Training Loss | Epoch | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----------------:|:--------:| |
|
| 0.8456 | 55 | 0.8537 | 0.8562 | |
|
| 0.7982 | 56 | 0.8021 | 0.8875 | |
|
| 0.8028 | 57 | 0.8028 | 0.8438 | |
|
|
|
The result of evaluation from trainer.evaluate(eval_dataset=emotion["test"]): |
|
|
|
{'eval_loss': 0.8208037614822388, 'eval_accuracy': 0.875, 'eval_runtime': 5.3137, 'eval_samples_per_second': 30.111, 'eval_steps_per_second': 0.941, 'epoch': 3.0} |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
