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distilbert-base-uncased-finetuned-ingredients

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  1. README.md +20 -13
  2. pytorch_model.bin +1 -1
  3. runs/Sep01_08-27-53_1ddac6225e97/1630484991.2188017/events.out.tfevents.1630484991.1ddac6225e97.74.1 +3 -0
  4. runs/Sep01_08-27-53_1ddac6225e97/events.out.tfevents.1630484991.1ddac6225e97.74.0 +3 -0
  5. runs/Sep01_08-27-53_1ddac6225e97/events.out.tfevents.1630485235.1ddac6225e97.74.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -22,16 +22,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9658580413297394
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  - name: Recall
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  type: recall
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- value: 0.9649910233393177
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  - name: F1
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  type: f1
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- value: 0.9654243376740009
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  - name: Accuracy
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  type: accuracy
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- value: 0.9921109555923145
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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
@@ -41,11 +41,11 @@ 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: 0.0246
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- - Precision: 0.9659
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- - Recall: 0.9650
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- - F1: 0.9654
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- - Accuracy: 0.9921
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  ## Model description
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@@ -70,15 +70,22 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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  ### Training results
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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 | 184 | 0.0562 | 0.9177 | 0.9309 | 0.9242 | 0.9833 |
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- | No log | 2.0 | 368 | 0.0287 | 0.9605 | 0.9605 | 0.9605 | 0.9905 |
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- | 0.1154 | 3.0 | 552 | 0.0246 | 0.9659 | 0.9650 | 0.9654 | 0.9921 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9740840035746202
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  - name: Recall
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  type: recall
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+ value: 0.9784560143626571
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  - name: F1
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  type: f1
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+ value: 0.9762651141961486
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9946558086270518
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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: 0.0164
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+ - Precision: 0.9741
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+ - Recall: 0.9785
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+ - F1: 0.9763
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+ - Accuracy: 0.9947
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  ## Model description
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  - seed: 42
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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: 10
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  ### Training results
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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 | 184 | 0.0439 | 0.9299 | 0.9408 | 0.9353 | 0.9855 |
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+ | No log | 2.0 | 368 | 0.0210 | 0.9650 | 0.9650 | 0.9650 | 0.9921 |
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+ | 0.1021 | 3.0 | 552 | 0.0208 | 0.9669 | 0.9704 | 0.9686 | 0.9930 |
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+ | 0.1021 | 4.0 | 736 | 0.0205 | 0.9677 | 0.9695 | 0.9686 | 0.9930 |
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+ | 0.1021 | 5.0 | 920 | 0.0159 | 0.9768 | 0.9829 | 0.9799 | 0.9957 |
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+ | 0.009 | 6.0 | 1104 | 0.0134 | 0.9777 | 0.9820 | 0.9798 | 0.9957 |
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+ | 0.009 | 7.0 | 1288 | 0.0149 | 0.9750 | 0.9785 | 0.9767 | 0.9947 |
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+ | 0.009 | 8.0 | 1472 | 0.0188 | 0.9723 | 0.9758 | 0.9740 | 0.9938 |
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+ | 0.0042 | 9.0 | 1656 | 0.0161 | 0.9759 | 0.9803 | 0.9781 | 0.9950 |
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+ | 0.0042 | 10.0 | 1840 | 0.0164 | 0.9741 | 0.9785 | 0.9763 | 0.9947 |
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  ### Framework versions
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