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distilbert-base-uncased-finetuned-ingredients

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Files changed (6) hide show
  1. README.md +9 -9
  2. pytorch_model.bin +1 -1
  3. runs/Aug31_10-15-21_5573dac4e2a4/1630404989.2200258/events.out.tfevents.1630404989.5573dac4e2a4.76.1 +3 -0
  4. runs/Aug31_10-15-21_5573dac4e2a4/events.out.tfevents.1630404989.5573dac4e2a4.76.0 +3 -0
  5. runs/Aug31_10-15-21_5573dac4e2a4/events.out.tfevents.1630405064.5573dac4e2a4.76.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9918144611186903
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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
@@ -32,11 +32,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ingredients_yes_no dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0264
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- - Precision: 0.9926
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- - Recall: 1.0
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- - F1: 0.9963
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- - Accuracy: 0.9918
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  ## Model description
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@@ -67,9 +67,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 170 | 0.0584 | 0.9739 | 0.9942 | 0.9839 | 0.9804 |
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- | No log | 2.0 | 340 | 0.0423 | 0.9861 | 1.0 | 0.9930 | 0.9870 |
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- | 0.123 | 3.0 | 510 | 0.0264 | 0.9926 | 1.0 | 0.9963 | 0.9918 |
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  ### Framework versions
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9929481628108375
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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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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ingredients_yes_no dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0262
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+ - Precision: 0.9914
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+ - Recall: 0.9986
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+ - F1: 0.9950
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+ - Accuracy: 0.9929
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 186 | 0.0566 | 0.9814 | 0.9885 | 0.9849 | 0.9827 |
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+ | No log | 2.0 | 372 | 0.0375 | 0.9864 | 0.9978 | 0.9921 | 0.9887 |
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+ | 0.113 | 3.0 | 558 | 0.0262 | 0.9914 | 0.9986 | 0.9950 | 0.9929 |
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  ### Framework versions
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