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eskayML/bert_interview_new

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  1. README.md +15 -15
  2. config.json +41 -21
  3. model.safetensors +2 -2
  4. tokenizer_config.json +1 -0
  5. training_args.bin +0 -0
README.md CHANGED
@@ -18,8 +18,8 @@ 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: 1.4570
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- - Accuracy: 0.8611
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  ## Model description
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@@ -50,21 +50,21 @@ 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 | 54 | 2.2496 | 0.2593 |
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- | No log | 2.0 | 108 | 2.1561 | 0.4444 |
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- | No log | 3.0 | 162 | 2.0315 | 0.5648 |
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- | No log | 4.0 | 216 | 1.9100 | 0.6852 |
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- | No log | 5.0 | 270 | 1.7820 | 0.7870 |
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- | No log | 6.0 | 324 | 1.6627 | 0.8056 |
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- | No log | 7.0 | 378 | 1.5728 | 0.8519 |
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- | No log | 8.0 | 432 | 1.5169 | 0.8611 |
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- | No log | 9.0 | 486 | 1.4705 | 0.8611 |
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- | 1.9122 | 10.0 | 540 | 1.4570 | 0.8611 |
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  ### Framework versions
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- - Transformers 4.46.2
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  - Pytorch 2.5.1+cu121
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- - Datasets 3.1.0
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- - Tokenizers 0.20.3
 
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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: 0.7181
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+ - Accuracy: 0.8362
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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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+ | 2.5731 | 1.0 | 579 | 2.3539 | 0.2888 |
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+ | 2.2431 | 2.0 | 1158 | 1.8700 | 0.4526 |
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+ | 1.8916 | 3.0 | 1737 | 1.5977 | 0.5302 |
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+ | 1.5897 | 4.0 | 2316 | 1.2684 | 0.6509 |
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+ | 1.485 | 5.0 | 2895 | 1.0863 | 0.6724 |
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+ | 1.282 | 6.0 | 3474 | 0.9135 | 0.7716 |
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+ | 1.0021 | 7.0 | 4053 | 0.8167 | 0.8103 |
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+ | 0.9446 | 8.0 | 4632 | 0.7997 | 0.8017 |
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+ | 0.8573 | 9.0 | 5211 | 0.7286 | 0.8319 |
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+ | 0.8327 | 10.0 | 5790 | 0.7181 | 0.8362 |
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  ### Framework versions
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+ - Transformers 4.47.1
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  - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
config.json CHANGED
@@ -9,29 +9,49 @@
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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,
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- "Finanicial Impact": 1,
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- "Health System Characteristics": 4,
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- "Imaging modalities in general": 2,
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- "Patient/Physican interaction in LUS": 9,
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- "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",
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.46.2",
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  "vocab_size": 30522
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  }
 
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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  "id2label": {
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+ "0": 0,
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+ "19": 19
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  },
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  "initializer_range": 0.02,
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  "label2id": {
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+ "0": 0,
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  },
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  "max_position_embeddings": 512,
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  "model_type": "distilbert",
 
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.47.1",
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  "vocab_size": 30522
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  }
model.safetensors CHANGED
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tokenizer_config.json CHANGED
@@ -44,6 +44,7 @@
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  "clean_up_tokenization_spaces": false,
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  "cls_token": "[CLS]",
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  "do_lower_case": true,
 
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  "mask_token": "[MASK]",
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  "max_length": 512,
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  "model_max_length": 512,
 
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  "clean_up_tokenization_spaces": false,
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  "cls_token": "[CLS]",
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  "do_lower_case": true,
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+ "extra_special_tokens": {},
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training_args.bin CHANGED
Binary files a/training_args.bin and b/training_args.bin differ