Upload TFBertForSequenceClassification
Browse files- README.md +46 -0
- config.json +35 -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: xtremedistil-l6-h256-uncased-nli
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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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# xtremedistil-l6-h256-uncased-nli
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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 4.31.0
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- TensorFlow 2.12.0
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "/content/drive/MyDrive/Models/alt_miniLM256",
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"architectures": [
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"BertForSequenceClassification"
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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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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 256,
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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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},
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"initializer_range": 0.02,
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"intermediate_size": 1024,
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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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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 8,
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"num_hidden_layers": 6,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.31.0",
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"type_vocab_size": 2,
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"use_cache": true,
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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 sha256:7d6194e8973e74eb82b2cf424b025b8a84c61b889933a24ecfae294a922f6cf5
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size 51152184
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