End of training

README.md

@@ -8,36 +8,29 @@ metrics:
 model-index:
 - name: fifi_classification
   results: []
-datasets:
-- mjbeattie/finditfixit
 ---
 
 <!-- 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. -->
 
 # fifi_classification
-## First load:  April 13, 2024
-## University of Oklahoma
 
-The city of Seattle uses a app called FindIt-FixIt to gather service requests from residents.  The requests routed to the responsible agency for resolution.  In 2023, we obtained the detail data from 2018-2023 in an effort to understand how COVID affected city services.  This data includes, among other things, detailed text from residents.  It also includes the service request type as chosen by the resident.  Text details and their corresponding categories are included in the dataset mjbeattie/finditfixit.
-
-This dataset was used to fine-tune [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) to classify text into one of the application's 15 service request types.  This model can be used to classify unseen texts.
-
-The model achieves the following results on the evaluation set:
-- Loss: 0.6323
-- Accuracy: 0.7987
+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: 0.6353
+- Accuracy: 0.8000
 
 ## Model description
 
-Classifies text into the 15 Seattle service request types.
+More information needed
 
 ## Intended uses & limitations
 
-Used for reclassifying service requests made prior to the introduction of the SPD-Unauthorized Encampment type.
+More information needed
 
 ## Training and evaluation data
 
-Trained and evaluated on mjbeattie/finditfixit
+More information needed
 
 ## Training procedure
 
@@ -56,15 +49,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.6326        | 1.0   | 2975  | 0.6031          | 0.7961   |
-| 0.4962        | 2.0   | 5950  | 0.5833          | 0.8029   |
-| 0.4335        | 3.0   | 8925  | 0.6113          | 0.8014   |
-| 0.3552        | 4.0   | 11900 | 0.6323          | 0.7987   |
+| 0.6323        | 1.0   | 2975  | 0.5987          | 0.7977   |
+| 0.4925        | 2.0   | 5950  | 0.5860          | 0.8027   |
+| 0.4248        | 3.0   | 8925  | 0.6092          | 0.8001   |
+| 0.353         | 4.0   | 11900 | 0.6353          | 0.8000   |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
-- Pytorch 2.2.1+cu121
-- Datasets 2.18.0
-- Tokenizers 0.15.2
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:07f1188c07191d807946016fb6bba3df709a8a7f4d1769fdba3be53f372571a6
+oid sha256:8eb5a6ad5cef1fff0f11b22d728d848f1630511f1a36b83d45cc0640705b7917
 size 267875632