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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-tiny-22k-384 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: 10-finetuned-spiderTraining50-200 |
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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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# 10-finetuned-spiderTraining50-200 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3858 |
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- Accuracy: 0.8899 |
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- Precision: 0.8906 |
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- Recall: 0.8904 |
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- F1: 0.8882 |
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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: 0.0005 |
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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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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.6006 | 1.0 | 125 | 1.3292 | 0.6246 | 0.6998 | 0.6230 | 0.6169 | |
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| 1.3122 | 2.0 | 250 | 1.0785 | 0.6747 | 0.7123 | 0.6769 | 0.6664 | |
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| 0.8869 | 3.0 | 375 | 0.9295 | 0.7367 | 0.7838 | 0.7398 | 0.7424 | |
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| 0.7394 | 4.0 | 500 | 0.6719 | 0.8078 | 0.8157 | 0.8089 | 0.8041 | |
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| 0.5704 | 5.0 | 625 | 0.6200 | 0.8198 | 0.8320 | 0.8265 | 0.8176 | |
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| 0.4273 | 6.0 | 750 | 0.5874 | 0.8338 | 0.8469 | 0.8338 | 0.8310 | |
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| 0.3289 | 7.0 | 875 | 0.5009 | 0.8549 | 0.8618 | 0.8523 | 0.8519 | |
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| 0.2828 | 8.0 | 1000 | 0.4697 | 0.8699 | 0.8728 | 0.8696 | 0.8677 | |
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| 0.2991 | 9.0 | 1125 | 0.4464 | 0.8639 | 0.8651 | 0.8653 | 0.8609 | |
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| 0.2108 | 10.0 | 1250 | 0.3858 | 0.8899 | 0.8906 | 0.8904 | 0.8882 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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