Khriis commited on
Commit
41938dd
1 Parent(s): c4e871c

Updated model

Browse files
Files changed (8) hide show
  1. README.md +2 -4
  2. config.json +10 -10
  3. merges.txt +0 -0
  4. model.safetensors +2 -2
  5. special_tokens_map.json +5 -49
  6. tokenizer_config.json +26 -26
  7. vocab.json +0 -0
  8. vocab.txt +0 -0
README.md CHANGED
@@ -1,7 +1,6 @@
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  ---
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  language:
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  - en
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- license: mit
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  tags:
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  - psychology
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  - emotion-recognition
@@ -10,7 +9,6 @@ tags:
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  - trigger-extraction
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  datasets:
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  - daily_dialog
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- inference: false
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  ---
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  # RECCON: Emotional Trigger Extraction Model
@@ -22,7 +20,7 @@ This repository contains the weights and custom inference handler to deploy RECC
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  ## 馃 Model Details
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  - **Task**: Extractive Question Answering (Span Extraction)
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- - **Base Model**: `roberta-base`
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  - **Training Dataset**: [RECCON Dataset](https://github.com/declare-lab/RECCON) (derived from DailyDialog)
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  - **Paper**: [Recognizing Emotion Cause in Conversations (Poria et al., 2021)](https://arxiv.org/abs/2012.11820)
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@@ -35,7 +33,7 @@ Ensure the following files are present in the root of this repository:
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  1. `handler.py`: The custom inference logic (included).
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  2. `requirements.txt`: Dependencies (included).
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  3. `model.safetensors` (or `pytorch_model.bin`): The model weights.
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- 4. `config.json`: The RoBERTa model configuration.
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  5. `tokenizer.json` / `vocab.json`: Tokenizer files.
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  ### Configuration
 
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  ---
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  language:
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  - en
 
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  tags:
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  - psychology
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  - emotion-recognition
 
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  - trigger-extraction
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  datasets:
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  - daily_dialog
 
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  ---
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  # RECCON: Emotional Trigger Extraction Model
 
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  ## 馃 Model Details
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  - **Task**: Extractive Question Answering (Span Extraction)
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+ - **Base Model**: `SpanBERT` (without context)
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  - **Training Dataset**: [RECCON Dataset](https://github.com/declare-lab/RECCON) (derived from DailyDialog)
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  - **Paper**: [Recognizing Emotion Cause in Conversations (Poria et al., 2021)](https://arxiv.org/abs/2012.11820)
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  1. `handler.py`: The custom inference logic (included).
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  2. `requirements.txt`: Dependencies (included).
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  3. `model.safetensors` (or `pytorch_model.bin`): The model weights.
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+ 4. `config.json`: The BERT model configuration.
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  5. `tokenizer.json` / `vocab.json`: Tokenizer files.
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  ### Configuration
config.json CHANGED
@@ -1,26 +1,26 @@
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  {
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  "architectures": [
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- "RobertaForQuestionAnswering"
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  ],
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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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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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- "max_position_embeddings": 514,
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- "model_type": "roberta",
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  "num_attention_heads": 12,
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  "num_hidden_layers": 12,
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- "pad_token_id": 1,
 
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  "position_embedding_type": "absolute",
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- "transformers_version": "4.57.1",
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- "type_vocab_size": 1,
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  "use_cache": true,
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- "vocab_size": 50265
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  }
 
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  }
merges.txt DELETED
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vocab.json DELETED
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vocab.txt ADDED
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