update model card README.md

README.md

@@ -7,30 +7,26 @@ model-index:
   results: []
 ---
 
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
 # NLP-reviews
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [Sentiment Labelled Sentences Data Set](https://archive.ics.uci.edu/ml/datasets/Sentiment+Labelled+Sentences). 
+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:
+- Loss: 0.3467
 
 ## Model description
 
-Given a sentence, this model will return the probabilities of it having a positive or negative sentiment, and the probabilities that it would be a review you would find from amazon.com, imdb.com, or yelp.com.
-
-It is a multi-label classification model which is able to determine both the sentiment of text and a grouping the text belongs to.
-
-## Training and evaluation data
-
-The data is obtained from the procured [Sentiment Labelled Sentences Data Set](https://archive.ics.uci.edu/ml/datasets/Sentiment+Labelled+Sentences).
+More information needed
 
-Each entry has a sentiment score: 1 for positive or 0 for negative.
+## Intended uses & limitations
 
-The data comes from one of three different websites:
-- amazon.com
-- imdb.com
-- yelp.com
+More information needed
 
-There are 500 positive and 500 negative sentences from each website, selected randomly from a larger dataset of reviews, and were chosen based on having clear positive or negative connotation. 
+## Training and evaluation data
 
-This was split into a 90-10 train-test split for model training and evaluation.
+More information needed
 
 ## Training procedure
 
@@ -43,15 +39,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3.0
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| No log        | 1.0   | 338  | 0.1837          |
-| 0.2194        | 2.0   | 676  | 0.1863          |
-| 0.048         | 3.0   | 1014 | 0.1952          |
+| No log        | 1.0   | 338  | 0.2270          |
+| 0.2235        | 2.0   | 676  | 0.2737          |
+| 0.0644        | 3.0   | 1014 | 0.3171          |
+| 0.0644        | 4.0   | 1352 | 0.3511          |
+| 0.0193        | 5.0   | 1690 | 0.3726          |
+| 0.0119        | 6.0   | 2028 | 0.3638          |
+| 0.0119        | 7.0   | 2366 | 0.3337          |
+| 0.0043        | 8.0   | 2704 | 0.3424          |
+| 0.0019        | 9.0   | 3042 | 0.3387          |
+| 0.0019        | 10.0  | 3380 | 0.3467          |
 
 
 ### Framework versions