add model
Browse files- README.md +47 -0
- config.json +31 -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_score
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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_score
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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 2.7.0
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- Datasets 1.18.3
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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_model/",
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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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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0
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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": "regression",
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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:a59ebd3290201fb2258837beced66e3bdeac494c33a93a39bcb797e3d65d68a8
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size 267953320
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