File size: 3,437 Bytes
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license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned
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-finetuned
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: 1.1657
- Logloss: 1.1657
- Accuracy: {'accuracy': 0.5808823529411765}
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Logloss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:---------------------------------:|
| No log | 0.9412 | 8 | 1.6072 | 1.6072 | {'accuracy': 0.18382352941176472} |
| 1.6101 | 2.0 | 17 | 1.5668 | 1.5668 | {'accuracy': 0.31985294117647056} |
| 1.5645 | 2.9412 | 25 | 1.5246 | 1.5246 | {'accuracy': 0.33455882352941174} |
| 1.4902 | 4.0 | 34 | 1.4774 | 1.4774 | {'accuracy': 0.4007352941176471} |
| 1.4243 | 4.9412 | 42 | 1.4283 | 1.4283 | {'accuracy': 0.44485294117647056} |
| 1.3502 | 6.0 | 51 | 1.3747 | 1.3747 | {'accuracy': 0.48161764705882354} |
| 1.3502 | 6.9412 | 59 | 1.3332 | 1.3332 | {'accuracy': 0.48161764705882354} |
| 1.2906 | 8.0 | 68 | 1.2978 | 1.2978 | {'accuracy': 0.5036764705882353} |
| 1.2371 | 8.9412 | 76 | 1.2702 | 1.2702 | {'accuracy': 0.5147058823529411} |
| 1.1856 | 10.0 | 85 | 1.2434 | 1.2434 | {'accuracy': 0.5404411764705882} |
| 1.1506 | 10.9412 | 93 | 1.2300 | 1.2300 | {'accuracy': 0.5477941176470589} |
| 1.0987 | 12.0 | 102 | 1.2088 | 1.2088 | {'accuracy': 0.5588235294117647} |
| 1.0758 | 12.9412 | 110 | 1.1949 | 1.1949 | {'accuracy': 0.5514705882352942} |
| 1.0758 | 14.0 | 119 | 1.1896 | 1.1896 | {'accuracy': 0.5588235294117647} |
| 1.0483 | 14.9412 | 127 | 1.1773 | 1.1773 | {'accuracy': 0.5698529411764706} |
| 1.0346 | 16.0 | 136 | 1.1719 | 1.1719 | {'accuracy': 0.5735294117647058} |
| 1.0215 | 16.9412 | 144 | 1.1702 | 1.1702 | {'accuracy': 0.5698529411764706} |
| 1.0177 | 18.0 | 153 | 1.1666 | 1.1666 | {'accuracy': 0.5772058823529411} |
| 0.9956 | 18.8235 | 160 | 1.1657 | 1.1657 | {'accuracy': 0.5808823529411765} |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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