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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-femto-1k-224 |
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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-convnextv2-femto-1k-224-finetuned-spiderTraining20-500 |
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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-convnextv2-femto-1k-224-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [facebook/convnextv2-femto-1k-224](https://huggingface.co./facebook/convnextv2-femto-1k-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4856 |
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- Accuracy: 0.8388 |
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- Precision: 0.8342 |
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- Recall: 0.8349 |
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- F1: 0.8332 |
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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: 25 |
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- eval_batch_size: 25 |
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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: 100 |
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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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| 1.9569 | 1.0 | 80 | 1.7758 | 0.5065 | 0.5330 | 0.5075 | 0.4959 | |
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| 1.05 | 2.0 | 160 | 0.9583 | 0.7207 | 0.7400 | 0.7158 | 0.7102 | |
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| 0.8342 | 3.0 | 240 | 0.7517 | 0.7568 | 0.7747 | 0.7420 | 0.7409 | |
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| 0.7 | 4.0 | 320 | 0.6801 | 0.7928 | 0.7921 | 0.7890 | 0.7826 | |
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| 0.5956 | 5.0 | 400 | 0.5913 | 0.8128 | 0.8130 | 0.8082 | 0.8061 | |
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| 0.572 | 6.0 | 480 | 0.5533 | 0.8278 | 0.8259 | 0.8223 | 0.8217 | |
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| 0.4786 | 7.0 | 560 | 0.5108 | 0.8348 | 0.8319 | 0.8308 | 0.8302 | |
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| 0.4201 | 8.0 | 640 | 0.5064 | 0.8318 | 0.8286 | 0.8248 | 0.8252 | |
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| 0.4486 | 9.0 | 720 | 0.4951 | 0.8408 | 0.8364 | 0.8363 | 0.8350 | |
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| 0.4382 | 10.0 | 800 | 0.4856 | 0.8388 | 0.8342 | 0.8349 | 0.8332 | |
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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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