New

.gitattributes

@@ -24,4 +24,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -18,38 +18,60 @@ It achieves the following results on the evaluation set:
 - Train Sparse Categorical Accuracy: 0.9836
 - Validation Loss: 0.4073
 - Validation Sparse Categorical Accuracy: 0.9583
-- Epoch: 2
+- Epoch: 3
 
 ## Model description
 
-Base model:  'bert-base-cased'
+Base model:  'bert-base-cased' can be used for intent classification. It trained on the [Intent-Classification-Commands](https://huggingface.co/datasets/dipesh/Intent-Classification-Commands) dataset. With the following classes-
+
+```
+{
+  "0": "asking date",
+  "1": "asking time",
+  "2": "asking weather",
+  "3": "check internet speed",
+  "4": "click photo",
+  "5": "covid cases",
+  "6": "download youtube video",
+  "7": "goodbye",
+  "8": "greet",
+  "9": "open website",
+  "10": "play games",
+  "11": "play on youtube",
+  "12": "send email",
+  "13": "send whatsapp message",
+  "14": "take screenshot",
+  "15": "tell me about",
+  "16": "tell me joke",
+  "17": "tell me news"
+}
+```
 
 ## Intended uses & limitations
 
-Intent Classifications for Chatbot or Virtual Assistant
+Intent Classifications for Chatbot or Virtual Assistant.
+Only supports the English language. It can't work in outside classes. But you can fine-tune it for your own use.
 
 ## Training and evaluation data
 
-More information needed
+Dataset Used: [Intent-Classification-Commands](https://huggingface.co/datasets/dipesh/Intent-Classification-Commands)
 
 ## Training procedure
 
-https://colab.research.google.com/drive/1tyXIbY875w0U8OuqEwfanecck5i-OfU6?usp=sharing
+https://colab.research.google.com/drive/1KHg14glvhdV_ziOcY0pHm66PBYoBZMS0?usp=sharing
 
 ### Training hyperparameters
 
+
 The following hyperparameters were used during training:
 - optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
 - training_precision: float32
 
 ### Training results
 
-| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
-|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
-| 2.5420     | 0.3224                            | 1.9997          | 0.6806                                 | 0     |
-| 1.4238     | 0.8684                            | 0.9106          | 0.9444                                 | 1     |
-| 0.6110     | 0.9836                            | 0.4073          | 0.9583                                 | 2     |
+![1.jpg](1.jpg)
 
+![2.jpg](2.jpg)
 
 ### Framework versions
 
@@ -57,3 +79,10 @@ The following hyperparameters were used during training:
 - TensorFlow 2.8.0
 - Datasets 2.2.2
 - Tokenizers 0.12.1
+
+
+## Connect me on-
+
+* Subscribe to me on: https://youtube.com/techportofficial
+
+* DM me on (for quick response): https://instagram.com/dipesh_pal17

config.json

@@ -1,59 +1,65 @@
-{'_name_or_path': 'bert-base-cased',
- 'architectures': ['BertForSequenceClassification'],
- 'attention_probs_dropout_prob': 0.1,
- 'classifier_dropout': None,
- 'gradient_checkpointing': False,
- 'hidden_act': 'gelu',
- 'hidden_dropout_prob': 0.1,
- 'hidden_size': 768,
- 'id2label': {'0': 'asking date',
-              '1': 'asking time',
-              '10': 'open website',
-              '11': 'play games',
-              '12': 'play on youtube',
-              '13': 'send email',
-              '14': 'send whatsapp message',
-              '15': 'take screenshot',
-              '16': 'tell me about',
-              '17': 'tell me joke',
-              '18': 'tell me news',
-              '2': 'asking weather',
-              '3': 'check internet speed',
-              '4': 'click photo',
-              '5': 'conversation',
-              '6': 'covid cases',
-              '7': 'download youtube video',
-              '8': 'goodbye',
-              '9': 'greet'},
- 'initializer_range': 0.02,
- 'intermediate_size': 3072,
- 'label2id': {'asking date': '0',
-              'asking time': '1',
-              'asking weather': '2',
-              'check internet speed': '3',
-              'click photo': '4',
-              'conversation': '5',
-              'covid cases': '6',
-              'download youtube video': '7',
-              'goodbye': '8',
-              'greet': '9',
-              'open website': '10',
-              'play games': '11',
-              'play on youtube': '12',
-              'send email': '13',
-              'send whatsapp message': '14',
-              'take screenshot': '15',
-              'tell me about': '16',
-              'tell me joke': '17',
-              'tell me news': '18'},
- 'layer_norm_eps': 1e-12,
- 'max_position_embeddings': 512,
- 'model_type': 'bert',
- 'num_attention_heads': 12,
- 'num_hidden_layers': 12,
- 'pad_token_id': 0,
- 'position_embedding_type': 'absolute',
- 'transformers_version': '4.19.2',
- 'type_vocab_size': 2,
- 'use_cache': True,
- 'vocab_size': 28996}
+{
+    "_name_or_path": "bert-base-cased",
+    "architectures": [
+        "BertForSequenceClassification"
+    ],
+    "attention_probs_dropout_prob": 0.1,
+    "classifier_dropout": null,
+    "gradient_checkpointing": false,
+    "hidden_act": "gelu",
+    "hidden_dropout_prob": 0.1,
+    "hidden_size": 768,
+    "id2label": {
+        "0": "asking date",
+        "1": "asking time",
+        "2": "asking weather",
+        "3": "check internet speed",
+        "4": "click photo",
+        "5": "covid cases",
+        "6": "download youtube video",
+        "7": "goodbye",
+        "8": "greet",
+        "9": "open website",
+        "10": "play games",
+        "11": "play on youtube",
+        "12": "send email",
+        "13": "send whatsapp message",
+        "14": "take screenshot",
+        "15": "tell me about",
+        "16": "tell me joke",
+        "17": "tell me news"
+    },
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "label2id": {
+        "asking date": "0",
+        "asking time": "1",
+        "asking weather": "2",
+        "check internet speed": "3",
+        "click photo": "4",
+        "covid cases": "5",
+        "download youtube video": "6",
+        "goodbye": "7",
+        "greet": "8",
+        "open website": "9",
+        "play games": "10",
+        "play on youtube": "11",
+        "send email": "12",
+        "send whatsapp message": "13",
+        "take screenshot": "14",
+        "tell me about": "15",
+        "tell me joke": "16",
+        "tell me news": "17"
+    },
+    "layer_norm_eps": 1e-12,
+    "max_position_embeddings": 512,
+    "model_type": "bert",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 12,
+    "pad_token_id": 0,
+    "position_embedding_type": "absolute",
+    "transformers_version": "4.19.2",
+    "type_vocab_size": 2,
+    "use_cache": true,
+    "vocab_size": 28996
+}

tf_model.h5

@@ -1,3 +1,3 @@
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-size 433587612
+oid sha256:60b1c53be86c50926d49749bada8891fb624d910c22d7a7e5becc3dde1300d54
+size 433584536