
<!-- 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-FBark-1k

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:
- Accuracy: 0.9792
- F1: 0.9808
- Loss: 0.0686
- Precision: 0.9788
- Recall: 0.9833

## 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: 0.0001
- 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: 35

### Training results



### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1

iinstia bijuga mangifera indica pterocarpus indicus roystonea regia tabebuia