GeneStory
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Classify-model-v1.2

Text Classification

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GeneStory commited on May 24

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README.md +11 -13
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README.md CHANGED Viewed

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [Alibaba-NLP/gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2915
-- Accuracy: 0.9375
 ## Model description
@@ -43,22 +43,20 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.0241        | 1.0   | 11   | 0.3903          | 0.8482   |
-| 0.2103        | 2.0   | 22   | 0.2814          | 0.8929   |
-| 0.0637        | 3.0   | 33   | 0.2157          | 0.9196   |
-| 0.023         | 4.0   | 44   | 0.2686          | 0.9375   |
-| 0.0147        | 5.0   | 55   | 0.3088          | 0.9286   |
-| 0.0091        | 6.0   | 66   | 0.2554          | 0.9375   |
-| 0.0055        | 7.0   | 77   | 0.2785          | 0.9464   |
-| 0.0054        | 8.0   | 88   | 0.2852          | 0.9464   |
-| 0.0033        | 9.0   | 99   | 0.2899          | 0.9375   |
-| 0.0034        | 10.0  | 110  | 0.2915          | 0.9375   |
 ### Framework versions

 This model is a fine-tuned version of [Alibaba-NLP/gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2901
+- Accuracy: 0.9464
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 8
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0269        | 1.0   | 11   | 0.3949          | 0.8482   |
+| 0.2124        | 2.0   | 22   | 0.2804          | 0.8929   |
+| 0.0651        | 3.0   | 33   | 0.2142          | 0.9107   |
+| 0.0224        | 4.0   | 44   | 0.2613          | 0.9196   |
+| 0.0111        | 5.0   | 55   | 0.3168          | 0.9375   |
+| 0.0082        | 6.0   | 66   | 0.2658          | 0.9464   |
+| 0.0053        | 7.0   | 77   | 0.2768          | 0.9464   |
+| 0.0049        | 8.0   | 88   | 0.2901          | 0.9464   |
 ### Framework versions

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