add model
Browse files- README.md +46 -0
- config.json +47 -0
- tf_model.h5 +3 -0
README.md
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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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- name: stress_classifier
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# stress_classifier
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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 2.6.1
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- Tokenizers 0.11.0
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config.json
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{
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"_name_or_path": "stress_classifier/",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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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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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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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_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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"LABEL_8": 8
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.16.2",
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"vocab_size": 30522
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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:da3a688b9af126320f6f818517e6927f3af73414d21d4fd969362034c1d88333
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size 267973400
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