mtyrrell
/

CPU_Economywide_Classifier

Text Classification

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mtyrrell commited on Jul 23, 2023

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update model card README.md

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@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1184
-- Precision Macro: 0.9615
-- Precision Weighted: 0.9630
-- Recall Macro: 0.9635
-- Recall Weighted: 0.9623
-- F1-score: 0.9621
-- Accuracy: 0.9623
 ## Model description
@@ -55,11 +55,11 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
-| No log        | 1.0   | 60   | 0.4189          | 0.9426          | 0.9442             | 0.9445       | 0.9434          | 0.9432   | 0.9434   |
-| No log        | 2.0   | 120  | 0.1438          | 0.9521          | 0.9531             | 0.9533       | 0.9528          | 0.9526   | 0.9528   |
-| No log        | 3.0   | 180  | 0.1119          | 0.9615          | 0.9630             | 0.9635       | 0.9623          | 0.9621   | 0.9623   |
-| No log        | 4.0   | 240  | 0.1477          | 0.9521          | 0.9531             | 0.9533       | 0.9528          | 0.9526   | 0.9528   |
-| No log        | 5.0   | 300  | 0.1184          | 0.9615          | 0.9630             | 0.9635       | 0.9623          | 0.9621   | 0.9623   |
 ### Framework versions

 This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1595
+- Precision Macro: 0.9521
+- Precision Weighted: 0.9531
+- Recall Macro: 0.9533
+- Recall Weighted: 0.9528
+- F1-score: 0.9526
+- Accuracy: 0.9528
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
+| No log        | 1.0   | 60   | 0.1380          | 0.9521          | 0.9531             | 0.9533       | 0.9528          | 0.9526   | 0.9528   |
+| No log        | 2.0   | 120  | 0.1855          | 0.9523          | 0.9545             | 0.9547       | 0.9528          | 0.9527   | 0.9528   |
+| No log        | 3.0   | 180  | 0.1977          | 0.9523          | 0.9545             | 0.9547       | 0.9528          | 0.9527   | 0.9528   |
+| No log        | 4.0   | 240  | 0.1249          | 0.9723          | 0.9718             | 0.9708       | 0.9717          | 0.9715   | 0.9717   |
+| No log        | 5.0   | 300  | 0.1595          | 0.9521          | 0.9531             | 0.9533       | 0.9528          | 0.9526   | 0.9528   |
 ### Framework versions