Update README.md

README.md

@@ -6,52 +6,33 @@ model-index:
   results: []
 ---
 
-<!-- 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. -->
-
-# bert-tv-portuguese
-
-This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Train Loss: 2.3734
-- Epoch: 8
+# BERT-TV
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
+BERT-TV is a BERT model specifically pre-trained from scratch on a dataset of television reviews in Brazilian Portuguese. 
+This model is tailored to grasp the nuances and specificities associated with the context and sentiment expressed in 
+television reviews. BERT-TV features 6 layers, 12 attention heads, and an embedding dimension of 768, making it adept at 
+handling NLP tasks related to television content in Portuguese.
 
-The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamW', 'weight_decay': 0.004, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.000102, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
-- training_precision: float32
+## Usage ideas
 
-### Training results
+- Sentiment analysis on television reviews in Portuguese
+- Recommender systems for television models in Portuguese
+- Text classification for different television brands and types in Portuguese
+- Named entity recognition in television-related contexts in Portuguese
+- Aspect extraction for features and specifications of televisions in Portuguese
+- Text generation for summarizing television reviews in Portuguese
 
-| Train Loss | Epoch |
-|:----------:|:-----:|
-| 6.3513     | 0     |
-| 4.4775     | 1     |
-| 3.5899     | 2     |
-| 3.1742     | 3     |
-| 2.9347     | 4     |
-| 2.7461     | 5     |
-| 2.5957     | 6     |
-| 2.4721     | 7     |
-| 2.3734     | 8     |
+## Limitations and bias
 
+As the BERT-TV model is exclusively pre-trained on television reviews in Brazilian Portuguese, its performance may be 
+limited when applied to other types of text or reviews in different languages. Furthermore, the model could inherit 
+biases present in the training data, which may influence its predictions or embeddings. The tokenizer is adapted from 
+the BERTimbau tokenizer, optimized for Brazilian Portuguese, thus it might not deliver optimal results with other 
+languages or Portuguese dialects.
 
-### Framework versions
+## Framework versions
 
 - Transformers 4.27.3
 - TensorFlow 2.11.1