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# dit-base-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5546
- Accuracy: 0.8022
- Recall: 0.8022
- F1: 0.7987
- Precision: 0.8055

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | Recall | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.4686        | 0.97  | 22   | 1.3367          | 0.4725   | 0.4725 | 0.4560 | 0.4932    |
| 1.2222        | 1.98  | 45   | 1.1007          | 0.5989   | 0.5989 | 0.6039 | 0.6760    |
| 1.0171        | 2.99  | 68   | 0.8868          | 0.6758   | 0.6758 | 0.6610 | 0.7054    |
| 0.8429        | 4.0   | 91   | 0.7198          | 0.7473   | 0.7473 | 0.7468 | 0.7525    |
| 0.7707        | 4.97  | 113  | 0.6289          | 0.7912   | 0.7912 | 0.7906 | 0.7972    |
| 0.6457        | 5.98  | 136  | 0.5813          | 0.7857   | 0.7857 | 0.7863 | 0.7961    |
| 0.5622        | 6.99  | 159  | 0.4907          | 0.8352   | 0.8352 | 0.8314 | 0.8451    |
| 0.5406        | 8.0   | 182  | 0.4951          | 0.8297   | 0.8297 | 0.8260 | 0.8318    |
| 0.5046        | 8.97  | 204  | 0.4709          | 0.8022   | 0.8022 | 0.7967 | 0.7980    |
| 0.5126        | 9.67  | 220  | 0.4974          | 0.8132   | 0.8132 | 0.8100 | 0.8207    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "recall", "f1", "precision"], "base_model": "microsoft/dit-base", "model-index": [{"name": "dit-base-finetuned-ind-5-balanced-1000", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8021978021978022, "name": "Accuracy"}, {"type": "recall", "value": 0.8021978021978022, "name": "Recall"}, {"type": "f1", "value": 0.7987160394100158, "name": "F1"}, {"type": "precision", "value": 0.8055448553047593, "name": "Precision"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/dit-base model-index autotrain_compatible endpoints_compatible region:us