|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224-in21k |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: test_model_94 |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# test_model_94 |
|
|
|
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 corranm/first_vote_100_per_new2 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8933 |
|
- F1 Macro: 0.0863 |
|
- F1 Micro: 0.2197 |
|
- F1 Weighted: 0.1195 |
|
- Precision Macro: 0.0630 |
|
- Precision Micro: 0.2197 |
|
- Precision Weighted: 0.0868 |
|
- Recall Macro: 0.1568 |
|
- Recall Micro: 0.2197 |
|
- Recall Weighted: 0.2197 |
|
- Accuracy: 0.2197 |
|
|
|
## 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: 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: 2 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:| |
|
| 1.9541 | 0.8 | 3 | 1.9150 | 0.0426 | 0.1591 | 0.0609 | 0.0263 | 0.1591 | 0.0377 | 0.1111 | 0.1591 | 0.1591 | 0.1591 | |
|
| 1.9037 | 1.8 | 6 | 1.8975 | 0.0848 | 0.2121 | 0.1175 | 0.0601 | 0.2121 | 0.0831 | 0.1520 | 0.2121 | 0.2121 | 0.2121 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.1 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
