Diwank Singh Tomer commited on
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Model files

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Signed-off-by: Diwank Singh Tomer <diwank.singh@gmail.com>

.ipynb_checkpoints/README-checkpoint.md ADDED
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+ ---
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+ license: mit
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+ ---
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+
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+ # diwank/silicone-deberta-pair
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+
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+ `deberta-large`-based dialog acts classifier. Trained on [silicone-merged](https://huggingface.co/datasets/diwank/silicone-merged): a simplified dialog act datasets from the silicone collection.
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+
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+ Takes two sentences as inputs (one previous and one current utterance of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. **Outputs one of 11 labels**:
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+
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+ ```python
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+ [
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+ (0, 'acknowledge')
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+ (1, 'answer')
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+ (2, 'backchannel')
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+ (3, 'reply_yes')
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+ (4, 'exclaim')
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+ (5, 'say')
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+ (6, 'reply_no')
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+ (7, 'hold')
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+ (8, 'ask')
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+ (9, 'intent')
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+ (10, 'ask_yes_no')
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+ ]
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+ ```
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+
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+ ## Example:
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+
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+ ```python
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+ from simpletransformers.classification import (
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+ ClassificationModel, ClassificationArgs
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+ )
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+
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+ model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")
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+ convert_to_label = lambda n: [
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+ ['acknowledge',
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+ 'answer',
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+ 'backchannel',
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+ 'reply_yes',
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+ 'exclaim',
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+ 'say',
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+ 'reply_no',
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+ 'hold',
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+ 'ask',
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+ 'intent',
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+ 'ask_yes_no'
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+ ][i] for i in n
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+ ]
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+
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+ predictions, raw_outputs = model.predict([["Say what is the meaning of life?", "I dont know"]])
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+ convert_to_label(predictions) # answer
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+
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+ ```
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+
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+
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+ ## Report from W&B
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+
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+ https://wandb.ai/diwank/da-silicone-combined/reports/silicone-deberta-pair--VmlldzoxNTczNjE5?accessToken=yj1jz4c365z0y5b3olgzye7qgsl7qv9lxvqhmfhtb6300hql6veqa5xiq1skn8ys
README.md CHANGED
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  ---
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  license: mit
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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  ---
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+
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+ # diwank/silicone-deberta-pair
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+
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+ `deberta-large`-based dialog acts classifier. Trained on [silicone-merged](https://huggingface.co/datasets/diwank/silicone-merged): a simplified dialog act datasets from the silicone collection.
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+
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+ Takes two sentences as inputs (one previous and one current utterance of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. **Outputs one of 11 labels**:
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+
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+ ```python
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+ [
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+ (0, 'acknowledge')
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+ (1, 'answer')
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+ (2, 'backchannel')
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+ (3, 'reply_yes')
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+ (4, 'exclaim')
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+ (5, 'say')
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+ (6, 'reply_no')
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+ (7, 'hold')
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+ (8, 'ask')
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+ (9, 'intent')
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+ (10, 'ask_yes_no')
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+ ]
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+ ```
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+
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+ ## Example:
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+
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+ ```python
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+ from simpletransformers.classification import (
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+ ClassificationModel, ClassificationArgs
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+ )
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+
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+ model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")
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+ convert_to_label = lambda n: [
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+ ['acknowledge',
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+ 'answer',
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+ 'backchannel',
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+ 'reply_yes',
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+ 'exclaim',
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+ 'say',
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+ 'reply_no',
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+ 'hold',
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+ 'ask',
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+ 'intent',
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+ 'ask_yes_no'
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+ ][i] for i in n
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+ ]
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+
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+ predictions, raw_outputs = model.predict([["Say what is the meaning of life?", "I dont know"]])
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+ convert_to_label(predictions) # answer
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+
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+ ```
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+
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+
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+ ## Report from W&B
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+
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+ https://wandb.ai/diwank/da-silicone-combined/reports/silicone-deberta-pair--VmlldzoxNTczNjE5?accessToken=yj1jz4c365z0y5b3olgzye7qgsl7qv9lxvqhmfhtb6300hql6veqa5xiq1skn8ys
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/deberta-large",
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+ "architectures": [
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+ "DebertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2",
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+ "3": "LABEL_3",
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+ "4": "LABEL_4",
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+ "5": "LABEL_5",
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+ "6": "LABEL_6",
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+ "7": "LABEL_7",
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+ "8": "LABEL_8",
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+ "9": "LABEL_9",
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+ "10": "LABEL_10"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_10": 10,
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+ "LABEL_2": 2,
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+ "LABEL_3": 3,
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+ "LABEL_4": 4,
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+ "LABEL_9": 9
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+ },
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "pad_token_id": 0,
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+ "pooler_dropout": 0,
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+ "pooler_hidden_act": "gelu",
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+ "pooler_hidden_size": 1024,
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+ "pos_att_type": [
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+ "c2p",
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+ "p2c"
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+ ],
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+ "position_biased_input": false,
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+ "relative_attention": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.16.2",
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+ "type_vocab_size": 0,
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+ "vocab_size": 50265
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+ }
eval_results.txt ADDED
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+ eval_loss = 0.39992852896930425
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+ mcc = 0.8192827881469071
merges.txt ADDED
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model_args.json ADDED
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