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 *.zip filter=lfs diff=lfs merge=lfs -text
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+finetuned-models/finetuned_on_product/distil-bert-fintuned-product-cfpb-complaints/saved_results/model_predictions_and_labels.csv filter=lfs diff=lfs merge=lfs -text

finetuned-models/finetuned_on_issue/distil-bert-fintuned-issues-cfpb-complaints/README.md

@@ -0,0 +1,67 @@
+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distil-bert-fintuned-issues-cfpb-complaints
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distil-bert-fintuned-issues-cfpb-complaints
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6711
+- Accuracy: 0.7652
+- Precision: 0.5935
+- Recall: 0.5577
+- F1: 0.5702
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.7269        | 1.0   | 11603 | 0.7187          | 0.7438   | 0.5853    | 0.5327 | 0.5491 |
+| 0.612         | 2.0   | 23206 | 0.6711          | 0.7652   | 0.5935    | 0.5577 | 0.5702 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0
+- Datasets 2.17.1
+- Tokenizers 0.15.2

finetuned-models/finetuned_on_issue/distil-bert-fintuned-issues-cfpb-complaints/checkpoint-11603/config.json

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+    "1": "Attempts to collect debt not owed",
+    "2": "Closing an account",
+    "3": "Closing your account",
+    "4": "Credit Report and Monitoring Issues",
+    "5": "Dealing with your lender or servicer",
+    "6": "Disputes and Misrepresentations",
+    "7": "Improper use of your report",
+    "8": "Incorrect information on your report",
+    "9": "Legal and Threat Actions",
+    "10": "Managing an account",
+    "11": "Payment and Funds Management",
+    "12": "Problem with a company's investigation into an existing issue",
+    "13": "Problem with a company's investigation into an existing problem",
+    "14": "Problem with a credit reporting company's investigation into an existing problem",
+    "15": "Problem with a purchase shown on your statement",
+    "16": "Written notification about debt"
+  },
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+    "Problem with a credit reporting company's investigation into an existing problem": 14,
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+    "Written notification about debt": 16
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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distil-bert-fintuned-product-cfpb-complaints
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distil-bert-fintuned-product-cfpb-complaints
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1393
+- Accuracy: 0.9595
+- Precision: 0.8788
+- Recall: 0.8175
+- F1: 0.8432
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1411        | 1.0   | 11603 | 0.1393          | 0.9595   | 0.8788    | 0.8175 | 0.8432 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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