Cippppy
/

mobilebert_trajectory_proof0

Text Classification

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Inference Endpoints

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Cippppy commited on Mar 1

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End of training

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 15160.7559
-- Accuracy: 0.6
 ## Model description
@@ -37,26 +37,34 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
 - 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 7    | 164888.375      | 0.4      |
-| No log        | 2.0   | 14   | 49532.4297      | 0.4      |
-| No log        | 3.0   | 21   | 38923.6992      | 0.6      |
-| No log        | 4.0   | 28   | 3229.375        | 0.35     |
-| No log        | 5.0   | 35   | 30543.9062      | 0.6      |
-| No log        | 6.0   | 42   | 43326.5703      | 0.4      |
-| No log        | 7.0   | 49   | 17400.2754      | 0.6      |
-| No log        | 8.0   | 56   | 15160.7559      | 0.6      |
 ### Framework versions

 This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 16478.7676
+- Accuracy: 0.7
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 2e-06
+- 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
+- num_epochs: 16
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 13   | 3802792.75      | 0.7      |
+| No log        | 2.0   | 26   | 3156379.5       | 0.7      |
+| No log        | 3.0   | 39   | 2625222.75      | 0.7      |
+| No log        | 4.0   | 52   | 2124862.75      | 0.7      |
+| No log        | 5.0   | 65   | 1716339.0       | 0.7      |
+| No log        | 6.0   | 78   | 1375630.5       | 0.7      |
+| No log        | 7.0   | 91   | 1055760.0       | 0.7      |
+| No log        | 8.0   | 104  | 741251.0        | 0.7      |
+| No log        | 9.0   | 117  | 451555.9375     | 0.7      |
+| No log        | 10.0  | 130  | 227678.9219     | 0.7      |
+| No log        | 11.0  | 143  | 82893.1172      | 0.7      |
+| No log        | 12.0  | 156  | 48836.0117      | 0.7      |
+| No log        | 13.0  | 169  | 33417.5430      | 0.7      |
+| No log        | 14.0  | 182  | 21012.9023      | 0.7      |
+| No log        | 15.0  | 195  | 17473.7871      | 0.7      |
+| No log        | 16.0  | 208  | 16478.7676      | 0.7      |
 ### Framework versions