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nystromformer-4096-medqa-usmle-MiniLM-IR-cs

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GBaker commited on Feb 12, 2023

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@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
 # nystromformer-4096-medqa-usmle-MiniLM-IR-cs
-This model is a fine-tuned version of [uw-madison/nystromformer-4096](https://huggingface.co/uw-madison/nystromformer-4096) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3876
-- Accuracy: 0.2820
 ## Model description
@@ -43,17 +43,22 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.99  | 79   | 1.3863          | 0.2372   |
-| No log        | 1.99  | 158  | 1.3861          | 0.2655   |
-| No log        | 2.99  | 237  | 1.3859          | 0.2545   |
-| No log        | 3.99  | 316  | 1.3837          | 0.2765   |
-| No log        | 4.99  | 395  | 1.3876          | 0.2820   |
 ### Framework versions

 # nystromformer-4096-medqa-usmle-MiniLM-IR-cs
+This model is a fine-tuned version of [GBaker/nystromformer-4096-medqa-usmle-MiniLM-IR-cs](https://huggingface.co/GBaker/nystromformer-4096-medqa-usmle-MiniLM-IR-cs) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.8436
+- Accuracy: 0.2812
 ## Model description
 - total_train_batch_size: 128
 - 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 | Accuracy | Validation Loss |
+|:-------------:|:-----:|:----:|:--------:|:---------------:|
+| No log        | 0.99  | 79   | 0.2372   | 1.3863          |
+| No log        | 1.99  | 158  | 0.2655   | 1.3861          |
+| No log        | 2.99  | 237  | 0.2545   | 1.3859          |
+| No log        | 3.99  | 316  | 0.2765   | 1.3837          |
+| No log        | 4.99  | 395  | 0.2820   | 1.3876          |
+| No log        | 5.99  | 474  | 1.3819   | 0.2639          |
+| 1.3342        | 6.99  | 553  | 1.4875   | 0.2694          |
+| 1.3342        | 7.99  | 632  | 1.6126   | 0.2718          |
+| 1.3342        | 8.99  | 711  | 1.7637   | 0.2804          |
+| 1.3342        | 9.99  | 790  | 1.8436   | 0.2812          |
 ### Framework versions