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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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- accuracy |
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model-index: |
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- name: 10k_test3_nli_finetuned_canine_c |
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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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# 10k_test3_nli_finetuned_canine_c |
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This model is a fine-tuned version of [google/canine-c](https://huggingface.co/google/canine-c) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0990 |
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- Accuracy: 0.3247 |
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- F1 Weighted: 0.1591 |
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- Precision Weighted: 0.1054 |
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- Recall Weighted: 0.3247 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | Precision Weighted | Recall Weighted | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:------------------:|:---------------:| |
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| 1.1017 | 1.0 | 312 | 1.1029 | 0.3247 | 0.1591 | 0.1054 | 0.3247 | |
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| 1.0999 | 2.0 | 625 | 1.0978 | 0.3533 | 0.1845 | 0.1248 | 0.3533 | |
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| 1.099 | 3.0 | 936 | 1.0990 | 0.3247 | 0.1591 | 0.1054 | 0.3247 | |
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### Framework versions |
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- Transformers 4.27.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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