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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: convnext-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# convnext-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
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This model is a fine-tuned version of [facebook/convnext-base-224](https://huggingface.co/facebook/convnext-base-224) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3443
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- Precision: 0.9864
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- Recall: 0.9822
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- F1: 0.9843
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- Accuracy: 0.9884
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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- label_smoothing_factor: 0.2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.3611 | 1.0 | 2021 | 0.3467 | 0.9843 | 0.9729 | 0.9784 | 0.9842 |
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| 0.3524 | 2.0 | 4042 | 0.3453 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
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| 0.3466 | 3.0 | 6063 | 0.3438 | 0.9854 | 0.9847 | 0.9851 | 0.9889 |
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| 0.3433 | 4.0 | 8084 | 0.3434 | 0.9850 | 0.9808 | 0.9829 | 0.9873 |
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| 0.3404 | 5.0 | 10105 | 0.3459 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
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| 0.3384 | 6.0 | 12126 | 0.3453 | 0.9853 | 0.9790 | 0.9821 | 0.9868 |
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| 0.3382 | 7.0 | 14147 | 0.3437 | 0.9864 | 0.9822 | 0.9843 | 0.9884 |
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| 0.3358 | 8.0 | 16168 | 0.3441 | 0.9857 | 0.9829 | 0.9843 | 0.9884 |
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| 0.3349 | 9.0 | 18189 | 0.3448 | 0.9857 | 0.9829 | 0.9843 | 0.9884 |
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| 0.3325 | 10.0 | 20210 | 0.3443 | 0.9864 | 0.9822 | 0.9843 | 0.9884 |
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### Framework versions
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- Transformers 4.22.2
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- Pytorch 1.12.1+cu113
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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