Text Classification
Transformers
TensorBoard
Safetensors
PyTorch
English
bert
fill-mask
emotion-classification
text-embeddings-inference
Instructions to use IsmaelMousa/bert-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IsmaelMousa/bert-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IsmaelMousa/bert-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IsmaelMousa/bert-finetuned-emotion") model = AutoModelForMaskedLM.from_pretrained("IsmaelMousa/bert-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- README.md +4 -4
- config.json +13 -15
README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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tags:
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- generated_from_trainer
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datasets:
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- emotion
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model-index:
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- name: bert-finetuned-emotion
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results: []
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language:
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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language:
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- en
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license: apache-2.0
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tags:
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- generated_from_trainer
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base_model: bert-base-cased
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datasets:
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- emotion
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pipeline_tag: text-classification
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model-index:
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- name: bert-finetuned-emotion
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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config.json
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"
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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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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "
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"1": "
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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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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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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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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.40.1",
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"type_vocab_size": 2,
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"use_cache": true,
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"BertForMaskedLM"
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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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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "sadness",
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"1": "joy",
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"2": "love",
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"3": "anger",
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"4": "fear",
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"5": "surprise"
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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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"anger": "3",
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"fear": "4",
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"joy": "1",
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"love": "2",
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"sadness": "0",
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"surprise": "5"
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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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"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": "4.40.1",
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"type_vocab_size": 2,
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"use_cache": true,
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