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evamaxfield commited on Jan 13, 2023

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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7833
-- F1: 0.5304
-- Accuracy: 0.6780
-- Precision: 0.5333
-- Recall: 0.5275
 ## Model description
@@ -43,8 +43,8 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 3e-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
@@ -54,11 +54,11 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
-| 0.5776        | 1.0   | 50   | 0.6066          | 0.3803 | 0.6667   | 0.5294    | 0.2967 |
-| 0.5545        | 2.0   | 100  | 0.6261          | 0.4331 | 0.6629   | 0.5152    | 0.3736 |
-| 0.4599        | 3.0   | 150  | 0.7046          | 0.5472 | 0.6364   | 0.4793    | 0.6374 |
-| 0.2527        | 4.0   | 200  | 0.7285          | 0.5521 | 0.6742   | 0.5248    | 0.5824 |
-| 0.2423        | 5.0   | 250  | 0.7833          | 0.5304 | 0.6780   | 0.5333    | 0.5275 |
 ### Framework versions

 This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.5558
+- F1: 0.5960
+- Accuracy: 0.7109
+- Precision: 0.5769
+- Recall: 0.6164
 ## Model description
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
+- train_batch_size: 12
+- eval_batch_size: 12
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
+| 0.5939        | 1.0   | 71   | 0.5989          | 0.0533 | 0.6635   | 1.0       | 0.0274 |
+| 0.5903        | 2.0   | 142  | 0.5558          | 0.5960 | 0.7109   | 0.5769    | 0.6164 |
+| 0.4613        | 3.0   | 213  | 0.6670          | 0.5641 | 0.6777   | 0.5301    | 0.6027 |
+| 0.4454        | 4.0   | 284  | 0.7647          | 0.5541 | 0.6872   | 0.5467    | 0.5616 |
+| 0.2931        | 5.0   | 355  | 0.8726          | 0.5139 | 0.6682   | 0.5211    | 0.5068 |
 ### Framework versions