eclec
/

patentClassfication2

Text Classification

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eclec commited on Sep 25, 2023

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update model card README.md

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@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6174
-- Accuracy: 0.6679
-- F1: 0.6763
 ## Model description
@@ -52,9 +52,9 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
-| 0.6489        | 1.0   | 4438  | 0.6401          | 0.6589   | 0.6221 |
-| 0.6055        | 2.0   | 8876  | 0.6174          | 0.6679   | 0.6763 |
-| 0.5566        | 3.0   | 13314 | 0.6250          | 0.6754   | 0.6839 |
 ### Framework versions

 This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.6121
+- Accuracy: 0.6746
+- F1: 0.6765
 ## Model description
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.6169        | 1.0   | 4438  | 0.6919          | 0.6121   | 0.6906 |
+| 0.5475        | 2.0   | 8876  | 0.6121          | 0.6746   | 0.6765 |
+| 0.4521        | 3.0   | 13314 | 0.7167          | 0.6706   | 0.6827 |
 ### Framework versions