|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/resnet-50 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: resnet-50-finetuned-hateful-meme-restructured-balanced |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: validation |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.522 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# resnet-50-finetuned-hateful-meme-restructured-balanced |
|
|
|
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6946 |
|
- Accuracy: 0.522 |
|
|
|
## 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: 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.6941 | 0.98 | 47 | 0.6947 | 0.494 | |
|
| 0.6906 | 1.99 | 95 | 0.6945 | 0.492 | |
|
| 0.6885 | 2.99 | 143 | 0.6951 | 0.492 | |
|
| 0.6873 | 4.0 | 191 | 0.6946 | 0.5 | |
|
| 0.6851 | 4.98 | 238 | 0.6941 | 0.516 | |
|
| 0.6813 | 5.99 | 286 | 0.6946 | 0.522 | |
|
| 0.6817 | 6.99 | 334 | 0.6955 | 0.508 | |
|
| 0.6849 | 8.0 | 382 | 0.6948 | 0.52 | |
|
| 0.6834 | 8.98 | 429 | 0.6953 | 0.508 | |
|
| 0.6758 | 9.84 | 470 | 0.6953 | 0.516 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|
