Update README.md

README.md

@@ -8,26 +8,19 @@ model-index:
   results: []
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-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
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 # bert-base-uncased-finetuned-glue-sst2
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
+Use for **sentiment analysis**.
 
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [glue sst2 dataset](https://huggingface.co/datasets/glue/viewer/sst2). The model achieves `91.39%` accuracy on the validation dataset.
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+[bert-base-uncased](https://huggingface.co/bert-base-uncased) is a pretrained English language model. `bert-base-uncased-finetuned-glue-sst2` adds a 2-class classification head for predicting `positive` and `negative` sentiment.
 
 ## Training and evaluation data
 
-More information needed
+The model has been trained on 10K training samples, even though the [glue sst2 dataset](https://huggingface.co/datasets/glue/viewer/sst2) contains 67.3K samples. This was done to decrease training time.
 
 ## Training procedure
 
@@ -39,7 +32,8 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-
+- Accuracy (training): `94.33%`
+- Accuracy (validation): `91.39%`
 
 ### Framework versions