jgammack
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MTL-distilbert-base-uncased

Fill-Mask Transformers PyTorch TensorBoard distilbert generated_from_trainer Inference Endpoints

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jgammack commited on Feb 7, 2022

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update model card README.md

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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.3718
 ## Model description
@@ -34,8 +34,8 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 15
-- eval_batch_size: 15
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -46,21 +46,21 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 3.1225        | 1.0   | 50   | 2.7381          |
-| 2.7945        | 2.0   | 100  | 2.6858          |
-| 2.7162        | 3.0   | 150  | 2.5329          |
-| 2.6526        | 4.0   | 200  | 2.5430          |
-| 2.5863        | 5.0   | 250  | 2.4785          |
-| 2.5701        | 6.0   | 300  | 2.4415          |
-| 2.5362        | 7.0   | 350  | 2.4678          |
-| 2.4961        | 8.0   | 400  | 2.4571          |
-| 2.4842        | 9.0   | 450  | 2.3915          |
-| 2.4697        | 10.0  | 500  | 2.4644          |
-| 2.4407        | 11.0  | 550  | 2.3628          |
-| 2.4264        | 12.0  | 600  | 2.4008          |
-| 2.4321        | 13.0  | 650  | 2.3672          |
-| 2.4169        | 14.0  | 700  | 2.3586          |
-| 2.4056        | 15.0  | 750  | 2.3705          |
 ### Framework versions

 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 2.0874
 ## Model description
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
+- train_batch_size: 7
+- eval_batch_size: 7
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
+| 2.5593        | 1.0   | 99   | 2.3163          |
+| 2.4346        | 2.0   | 198  | 2.2918          |
+| 2.3377        | 3.0   | 297  | 2.2345          |
+| 2.2953        | 4.0   | 396  | 2.1463          |
+| 2.2296        | 5.0   | 495  | 2.1761          |
+| 2.2235        | 6.0   | 594  | 2.0721          |
+| 2.1878        | 7.0   | 693  | 2.1460          |
+| 2.1569        | 8.0   | 792  | 2.0856          |
+| 2.1455        | 9.0   | 891  | 2.1039          |
+| 2.1391        | 10.0  | 990  | 2.1112          |
+| 2.1056        | 11.0  | 1089 | 2.0694          |
+| 2.1076        | 12.0  | 1188 | 2.0501          |
+| 2.0919        | 13.0  | 1287 | 2.0484          |
+| 2.0669        | 14.0  | 1386 | 2.0342          |
+| 2.0595        | 15.0  | 1485 | 2.0802          |
 ### Framework versions