add model
Browse files- README.md +9 -50
- config.json +64 -64
- tf_model.h5 +3 -0
README.md
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license: apache-2.0
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- generated_from_keras_callback
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model-index:
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# Intent-Classification-Bert-Base-Cased
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This model
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It achieves the following results on the evaluation set:
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- Train Sparse Categorical Accuracy: 0.9836
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- Validation Loss: 0.4073
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- Validation Sparse Categorical Accuracy: 0.9583
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- Epoch: 3
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## Model description
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```
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{
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"0": "asking date",
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"1": "asking time",
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"2": "asking weather",
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"3": "check internet speed",
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"4": "click photo",
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"5": "covid cases",
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"6": "download youtube video",
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"7": "goodbye",
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"8": "greet",
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"9": "open website",
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"10": "play games",
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"11": "play on youtube",
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"12": "send email",
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"13": "send whatsapp message",
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"14": "take screenshot",
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"15": "tell me about",
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"16": "tell me joke",
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"17": "tell me news"
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}
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```
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## Intended uses & limitations
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Only supports the English language. It can't work in outside classes. But you can fine-tune it for your own use.
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## Training and evaluation data
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## Training procedure
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https://colab.research.google.com/drive/1KHg14glvhdV_ziOcY0pHm66PBYoBZMS0?usp=sharing
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer:
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- training_precision: float32
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### Training results
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![1.jpg](1.jpg)
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![2.jpg](2.jpg)
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### Framework versions
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- Transformers 4.
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- TensorFlow 2.
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- Datasets 2.2.2
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- Tokenizers 0.
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## Connect me on-
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* Subscribe to me on: https://youtube.com/techportofficial
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* DM me on (for quick response): https://instagram.com/dipesh_pal17
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---
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tags:
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- generated_from_keras_callback
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model-index:
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# Intent-Classification-Bert-Base-Cased
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: None
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- training_precision: float32
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### Training results
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### Framework versions
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- Transformers 4.16.2
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- TensorFlow 2.9.1
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- Datasets 2.2.2
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- Tokenizers 0.10.3
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config.json
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}
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{
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"_name_or_path": "models/Intent-Classification-Bert-Base-Cased/",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "asking date",
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"1": "asking time",
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"2": "asking weather",
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"3": "check internet speed",
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"4": "click photo",
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"5": "covid cases",
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"6": "download youtube video",
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"7": "goodbye",
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"8": "greet",
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"9": "open website",
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"10": "play games",
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"11": "play on youtube",
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"12": "send email",
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"13": "send whatsapp message",
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"14": "take screenshot",
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"15": "tell me about",
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"16": "tell me joke",
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"17": "tell me news"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"asking date": "0",
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"asking time": "1",
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"asking weather": "2",
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"check internet speed": "3",
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"click photo": "4",
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"covid cases": "5",
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"download youtube video": "6",
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"goodbye": "7",
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"greet": "8",
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"open website": "9",
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"play games": "10",
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"play on youtube": "11",
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"send email": "12",
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"send whatsapp message": "13",
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"take screenshot": "14",
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"tell me about": "15",
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"tell me joke": "16",
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"tell me news": "17"
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.16.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:4bdb112ddf8fe06dcbf3e3b1be8cf82388656f89126fc3f6351e2afda583e4c7
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size 433584536
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