| | --- |
| | license: apache-2.0 |
| | base_model: facebook/convnextv2-tiny-22k-384 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: t5spiders |
| | 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. --> |
| |
|
| | # t5spiders |
| |
|
| | This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4612 |
| | - Accuracy: 0.9 |
| | - Precision: 0.9035 |
| | - Recall: 0.9103 |
| | - F1: 0.9024 |
| |
|
| | ## 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 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | No log | 0.96 | 6 | 1.1803 | 0.68 | 0.6789 | 0.6869 | 0.6751 | |
| | | 1.3235 | 1.92 | 12 | 0.7862 | 0.84 | 0.8603 | 0.8570 | 0.8388 | |
| | | 1.3235 | 2.88 | 18 | 0.5749 | 0.9 | 0.9035 | 0.9103 | 0.9024 | |
| | | 0.6609 | 4.0 | 25 | 0.4798 | 0.9 | 0.9035 | 0.9103 | 0.9024 | |
| | | 0.43 | 4.8 | 30 | 0.4612 | 0.9 | 0.9035 | 0.9103 | 0.9024 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.33.3 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| |
|
