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eskayML
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interview_classifier

Text Classification
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distilbert
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eskayML/interview_classifier

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  1. README.md +22 -22
  2. config.json +20 -20
  3. model.safetensors +1 -1
  4. runs/Jul04_10-06-36_0e9ed6c0f9ab/events.out.tfevents.1720087599.0e9ed6c0f9ab.907.0 +0 -0
  5. runs/Jul04_10-07-52_0e9ed6c0f9ab/events.out.tfevents.1720087673.0e9ed6c0f9ab.907.1 +0 -0
  6. runs/Jul04_10-16-28_0e9ed6c0f9ab/events.out.tfevents.1720088188.0e9ed6c0f9ab.907.2 +0 -0
  7. training_args.bin +0 -0
README.md CHANGED
@@ -17,8 +17,8 @@ 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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1239
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- - Accuracy: 0.9603
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  ## Model description
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@@ -49,26 +49,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 76 | 2.1645 | 0.1921 |
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- | No log | 2.0 | 152 | 1.8505 | 0.4238 |
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- | No log | 3.0 | 228 | 1.4303 | 0.6887 |
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- | No log | 4.0 | 304 | 1.0770 | 0.7682 |
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- | No log | 5.0 | 380 | 0.8012 | 0.8477 |
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- | No log | 6.0 | 456 | 0.6188 | 0.8609 |
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- | 1.4872 | 7.0 | 532 | 0.4291 | 0.9205 |
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- | 1.4872 | 8.0 | 608 | 0.3219 | 0.9338 |
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- | 1.4872 | 9.0 | 684 | 0.2561 | 0.9536 |
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- | 1.4872 | 10.0 | 760 | 0.2071 | 0.9536 |
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- | 1.4872 | 11.0 | 836 | 0.1758 | 0.9603 |
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- | 1.4872 | 12.0 | 912 | 0.1486 | 0.9603 |
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- | 1.4872 | 13.0 | 988 | 0.1443 | 0.9603 |
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- | 0.3011 | 14.0 | 1064 | 0.1384 | 0.9603 |
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- | 0.3011 | 15.0 | 1140 | 0.1377 | 0.9603 |
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- | 0.3011 | 16.0 | 1216 | 0.1347 | 0.9603 |
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- | 0.3011 | 17.0 | 1292 | 0.1267 | 0.9603 |
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- | 0.3011 | 18.0 | 1368 | 0.1223 | 0.9603 |
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- | 0.3011 | 19.0 | 1444 | 0.1256 | 0.9603 |
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- | 0.1494 | 20.0 | 1520 | 0.1239 | 0.9603 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0333
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+ - Accuracy: 1.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 54 | 2.2119 | 0.1852 |
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+ | No log | 2.0 | 108 | 2.0620 | 0.3704 |
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+ | No log | 3.0 | 162 | 1.7627 | 0.7037 |
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+ | No log | 4.0 | 216 | 1.4448 | 0.7685 |
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+ | No log | 5.0 | 270 | 1.1397 | 0.8889 |
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+ | No log | 6.0 | 324 | 0.8434 | 0.9167 |
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+ | No log | 7.0 | 378 | 0.6044 | 0.9444 |
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+ | No log | 8.0 | 432 | 0.4223 | 0.9907 |
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+ | No log | 9.0 | 486 | 0.2967 | 0.9907 |
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+ | 1.3767 | 10.0 | 540 | 0.2077 | 0.9907 |
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+ | 1.3767 | 11.0 | 594 | 0.1528 | 1.0 |
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+ | 1.3767 | 12.0 | 648 | 0.1135 | 1.0 |
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+ | 1.3767 | 13.0 | 702 | 0.0851 | 1.0 |
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+ | 1.3767 | 14.0 | 756 | 0.0661 | 1.0 |
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+ | 1.3767 | 15.0 | 810 | 0.0548 | 1.0 |
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+ | 1.3767 | 16.0 | 864 | 0.0449 | 1.0 |
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+ | 1.3767 | 17.0 | 918 | 0.0399 | 1.0 |
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+ | 1.3767 | 18.0 | 972 | 0.0358 | 1.0 |
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+ | 0.1191 | 19.0 | 1026 | 0.0339 | 1.0 |
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+ | 0.1191 | 20.0 | 1080 | 0.0333 | 1.0 |
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  ### Framework versions
config.json CHANGED
@@ -9,29 +9,29 @@
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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  "id2label": {
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- "0": "Value equation",
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- "1": "Credentialing / Quality Assurance Infrastructure",
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- "2": "Finanicial Impact",
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- "3": "Health System Characteristics",
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- "4": "Clinical utility & efficiency-Provider perspective",
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- "5": "Workflow related problems",
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- "6": "Provider Characteristics",
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- "7": "Training",
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- "8": "Patient/Physican interaction in LUS",
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- "9": "Imaging modalities in general"
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  },
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  "initializer_range": 0.02,
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  "label2id": {
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- "Clinical utility & efficiency-Provider perspective": 4,
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- "Credentialing / Quality Assurance Infrastructure": 1,
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- "Finanicial Impact": 2,
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- "Health System Characteristics": 3,
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- "Imaging modalities in general": 9,
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- "Patient/Physican interaction in LUS": 8,
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- "Provider Characteristics": 6,
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- "Training": 7,
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- "Value equation": 0,
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- "Workflow related problems": 5
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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": "Provider Characteristics",
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+ "1": "Finanicial Impact",
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+ "2": "Imaging modalities in general",
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+ "3": "Clinical utility & efficiency-Provider perspective",
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+ "4": "Health System Characteristics",
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+ "5": "Training",
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+ "6": "Value equation",
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+ "7": "Workflow related problems",
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+ "8": "Credentialing / Quality Assurance Infrastructure",
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+ "9": "Patient/Physican interaction in LUS"
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  },
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  "initializer_range": 0.02,
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  "label2id": {
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+ "Clinical utility & efficiency-Provider perspective": 3,
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+ "Credentialing / Quality Assurance Infrastructure": 8,
27
+ "Finanicial Impact": 1,
28
+ "Health System Characteristics": 4,
29
+ "Imaging modalities in general": 2,
30
+ "Patient/Physican interaction in LUS": 9,
31
+ "Provider Characteristics": 0,
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+ "Training": 5,
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+ "Value equation": 6,
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+ "Workflow related problems": 7
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  },
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  "max_position_embeddings": 512,
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  "model_type": "distilbert",
model.safetensors CHANGED
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