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  1. README.md +64 -0
  2. config.json +39 -0
  3. model.safetensors +3 -0
  4. runs/Feb25_06-51-31_d45e614e63bd/events.out.tfevents.1708843901.d45e614e63bd.218.0 +3 -0
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  20. tokenizer.json +0 -0
  21. tokenizer_config.json +58 -0
  22. training_args.bin +3 -0
  23. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: sentence-transformers/bert-base-nli-mean-tokens
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: mbti-bert-nli-finetuned_v2
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # mbti-bert-nli-finetuned_v2
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+
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+ This model is a fine-tuned version of [sentence-transformers/bert-base-nli-mean-tokens](https://huggingface.co/sentence-transformers/bert-base-nli-mean-tokens) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5429
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+ - F1: 0.5231
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+ - Roc Auc: 0.6546
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
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+ | 0.5413 | 1.0 | 5948 | 0.5385 | 0.5721 | 0.6766 |
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+ | 0.5046 | 2.0 | 11896 | 0.5429 | 0.5231 | 0.6546 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.0+cu121
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+ - Tokenizers 0.15.2
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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": 12,
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+ "num_hidden_layers": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "multi_label_classification",
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+ "torch_dtype": "float32",
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+ "type_vocab_size": 2,
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