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distilbert-base-uncased-finetuned-ingredients

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add model

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Files changed (7) hide show
  1. README.md +12 -12
  2. config.json +10 -10
  3. pytorch_model.bin +1 -1
  4. runs/Aug31_15-27-21_6005f014a2a9/1630423772.9026814/events.out.tfevents.1630423772.6005f014a2a9.74.1 +3 -0
  5. runs/Aug31_15-27-21_6005f014a2a9/events.out.tfevents.1630423772.6005f014a2a9.74.0 +3 -0
  6. runs/Aug31_15-27-21_6005f014a2a9/events.out.tfevents.1630423849.6005f014a2a9.74.2 +3 -0
  7. 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: 0.9878658101356174
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  - name: Recall
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  type: recall
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- value: 0.9985569985569985
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  - name: F1
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  type: f1
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- value: 0.9931826336562611
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  - name: Accuracy
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  type: accuracy
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- value: 0.9928244463689224
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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: 0.0280
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- - Precision: 0.9879
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- - Recall: 0.9986
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- - F1: 0.9932
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- - Accuracy: 0.9928
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  ## Model description
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@@ -76,9 +76,9 @@ 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 | 186 | 0.0612 | 0.9807 | 0.9899 | 0.9853 | 0.9821 |
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- | No log | 2.0 | 372 | 0.0390 | 0.9836 | 0.9935 | 0.9885 | 0.9890 |
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- | 0.1179 | 3.0 | 558 | 0.0280 | 0.9879 | 0.9986 | 0.9932 | 0.9928 |
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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: 0.9658580413297394
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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
 
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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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  | 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
config.json CHANGED
@@ -9,19 +9,19 @@
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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  "id2label": {
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- "0": "ADD-B",
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- "1": "ADD-C",
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- "2": "REM-B",
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- "3": "REM-C",
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- "4": "O"
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  },
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  "initializer_range": 0.02,
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  "label2id": {
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- "ADD-C": 1,
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- "O": 4,
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- "REM-B": 2,
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- "REM-C": 3
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  },
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  "max_position_embeddings": 512,
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  "model_type": "distilbert",
 
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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  "id2label": {
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+ "0": "O",
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+ "3": "B-REM",
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  },
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  "initializer_range": 0.02,
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  "label2id": {
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+ "B-ADD": 1,
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+ "B-REM": 3,
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+ "I-ADD": 2,
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+ "I-REM": 4,
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+ "O": 0
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  },
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  "max_position_embeddings": 512,
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  "model_type": "distilbert",
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