---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass18
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8678571428571429
---

<!-- 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. -->

# weeds_hfclass18

This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4372
- Accuracy: 0.8679

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4335        | 1.0   | 69   | 2.4087          | 0.2375   |
| 2.3043        | 2.0   | 138  | 2.2215          | 0.3339   |
| 1.8342        | 3.0   | 207  | 1.6984          | 0.5786   |
| 1.4059        | 4.0   | 276  | 1.1954          | 0.6804   |
| 1.0081        | 5.0   | 345  | 0.8756          | 0.7482   |
| 0.8916        | 6.0   | 414  | 0.6818          | 0.8232   |
| 0.7313        | 7.0   | 483  | 0.5369          | 0.8482   |
| 0.6677        | 8.0   | 552  | 0.5223          | 0.8554   |
| 0.6206        | 9.0   | 621  | 0.4609          | 0.8732   |
| 0.6543        | 10.0  | 690  | 0.4372          | 0.8679   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2