---
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-base-1k-224-for-pre_evaluation
  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. -->

# convnextv2-base-1k-224-for-pre_evaluation

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4479
- Accuracy: 0.4382

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5952        | 0.93  | 10   | 1.5511          | 0.2960   |
| 1.5238        | 1.95  | 21   | 1.5091          | 0.3427   |
| 1.4881        | 2.98  | 32   | 1.4854          | 0.3450   |
| 1.4708        | 4.0   | 43   | 1.4616          | 0.3473   |
| 1.4361        | 4.93  | 53   | 1.4417          | 0.3450   |
| 1.3764        | 5.95  | 64   | 1.4135          | 0.3753   |
| 1.3333        | 6.98  | 75   | 1.3822          | 0.3986   |
| 1.3296        | 8.0   | 86   | 1.4112          | 0.3636   |
| 1.2798        | 8.93  | 96   | 1.4038          | 0.3893   |
| 1.3129        | 9.95  | 107  | 1.4241          | 0.3776   |
| 1.3014        | 10.98 | 118  | 1.3570          | 0.3893   |
| 1.2332        | 12.0  | 129  | 1.4073          | 0.3893   |
| 1.212         | 12.93 | 139  | 1.3770          | 0.4033   |
| 1.1763        | 13.95 | 150  | 1.3891          | 0.3963   |
| 1.124         | 14.98 | 161  | 1.3915          | 0.4126   |
| 1.0963        | 16.0  | 172  | 1.4099          | 0.4149   |
| 1.0547        | 16.93 | 182  | 1.4206          | 0.4033   |
| 1.0631        | 17.95 | 193  | 1.4041          | 0.4196   |
| 0.9911        | 18.98 | 204  | 1.4272          | 0.4149   |
| 1.005         | 20.0  | 215  | 1.4211          | 0.4219   |
| 0.9663        | 20.93 | 225  | 1.4662          | 0.4009   |
| 0.9533        | 21.95 | 236  | 1.4286          | 0.4336   |
| 0.9506        | 22.98 | 247  | 1.4135          | 0.4312   |
| 0.8973        | 24.0  | 258  | 1.4428          | 0.4266   |
| 0.8807        | 24.93 | 268  | 1.4479          | 0.4382   |
| 0.8731        | 25.95 | 279  | 1.4429          | 0.4289   |
| 0.8472        | 26.98 | 290  | 1.4461          | 0.4312   |
| 0.8348        | 27.91 | 300  | 1.4531          | 0.4336   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3