emdemor
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question-generator

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emdemor commited on Aug 19

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@@ -18,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5860
 ## Model description
@@ -37,26 +37,35 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 1
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 1.9237        | 0.16  | 20   | 1.8701          |
-| 1.8479        | 0.32  | 40   | 1.7706          |
-| 1.7419        | 0.48  | 60   | 1.6614          |
-| 1.674         | 0.64  | 80   | 1.6176          |
-| 1.6024        | 0.8   | 100  | 1.5984          |
-| 1.6203        | 0.96  | 120  | 1.5860          |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.4475
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 0.0005
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
+| 1.8852        | 0.08  | 50   | 1.7072          |
+| 1.6036        | 0.16  | 100  | 1.4856          |
+| 1.5186        | 0.24  | 150  | 1.4662          |
+| 1.4822        | 0.32  | 200  | 1.4603          |
+| 1.5035        | 0.4   | 250  | 1.4578          |
+| 1.4813        | 0.48  | 300  | 1.4558          |
+| 1.4878        | 0.56  | 350  | 1.4534          |
+| 1.4765        | 0.64  | 400  | 1.4523          |
+| 1.4803        | 0.72  | 450  | 1.4485          |
+| 1.4925        | 0.8   | 500  | 1.4478          |
+| 1.49          | 0.88  | 550  | 1.4467          |
+| 1.4888        | 0.96  | 600  | 1.4461          |
+| 1.4732        | 1.04  | 650  | 1.4470          |
+| 1.4677        | 1.12  | 700  | 1.4476          |
+| 1.4402        | 1.2   | 750  | 1.4475          |
 ### Framework versions