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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnext-tiny-224_album_vitVMMRdb_make_model_album_pred
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. -->
# convnext-tiny-224_album_vitVMMRdb_make_model_album_pred
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7021
- Accuracy: 0.8173
- Precision: 0.8094
- Recall: 0.8173
- F1: 0.8057
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 4.6105 | 1.0 | 839 | 4.5248 | 0.1097 | 0.0579 | 0.1097 | 0.0403 |
| 3.4711 | 2.0 | 1678 | 3.3162 | 0.3000 | 0.2302 | 0.3000 | 0.2097 |
| 2.6202 | 3.0 | 2517 | 2.4445 | 0.4709 | 0.4120 | 0.4709 | 0.3939 |
| 2.0614 | 4.0 | 3356 | 1.8839 | 0.5742 | 0.5389 | 0.5742 | 0.5168 |
| 1.7026 | 5.0 | 4195 | 1.5247 | 0.6436 | 0.6180 | 0.6436 | 0.6013 |
| 1.4288 | 6.0 | 5034 | 1.2768 | 0.6979 | 0.6810 | 0.6979 | 0.6686 |
| 1.1953 | 7.0 | 5873 | 1.0960 | 0.7323 | 0.7218 | 0.7323 | 0.7077 |
| 1.058 | 8.0 | 6712 | 0.9828 | 0.7548 | 0.7441 | 0.7548 | 0.7350 |
| 0.9691 | 9.0 | 7551 | 0.9018 | 0.7718 | 0.7616 | 0.7718 | 0.7536 |
| 0.8757 | 10.0 | 8390 | 0.8380 | 0.7893 | 0.7806 | 0.7893 | 0.7756 |
| 0.8446 | 11.0 | 9229 | 0.7905 | 0.7982 | 0.7913 | 0.7982 | 0.7859 |
| 0.7711 | 12.0 | 10068 | 0.7524 | 0.8069 | 0.7995 | 0.8069 | 0.7950 |
| 0.7689 | 13.0 | 10907 | 0.7283 | 0.8123 | 0.8043 | 0.8123 | 0.8009 |
| 0.6919 | 14.0 | 11746 | 0.7133 | 0.8148 | 0.8061 | 0.8148 | 0.8036 |
| 0.694 | 15.0 | 12585 | 0.7064 | 0.8177 | 0.8089 | 0.8177 | 0.8067 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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