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---
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
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