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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: convnext-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
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-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
This model is a fine-tuned version of [facebook/convnext-base-224](https://huggingface.co/facebook/convnext-base-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3443
- Precision: 0.9864
- Recall: 0.9822
- F1: 0.9843
- Accuracy: 0.9884
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3611 | 1.0 | 2021 | 0.3467 | 0.9843 | 0.9729 | 0.9784 | 0.9842 |
| 0.3524 | 2.0 | 4042 | 0.3453 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
| 0.3466 | 3.0 | 6063 | 0.3438 | 0.9854 | 0.9847 | 0.9851 | 0.9889 |
| 0.3433 | 4.0 | 8084 | 0.3434 | 0.9850 | 0.9808 | 0.9829 | 0.9873 |
| 0.3404 | 5.0 | 10105 | 0.3459 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
| 0.3384 | 6.0 | 12126 | 0.3453 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
| 0.3382 | 7.0 | 14147 | 0.3437 | 0.9864 | 0.9822 | 0.9843 | 0.9884 |
| 0.3358 | 8.0 | 16168 | 0.3441 | 0.9857 | 0.9829 | 0.9843 | 0.9884 |
| 0.3349 | 9.0 | 18189 | 0.3448 | 0.9857 | 0.9829 | 0.9843 | 0.9884 |
| 0.3325 | 10.0 | 20210 | 0.3443 | 0.9864 | 0.9822 | 0.9843 | 0.9884 |
### Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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