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stackoverflow_tag_classification/initial_run/deberta-v3-xsmall/unique-ape-807

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  1. README.md +68 -0
  2. config.json +90 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: microsoft/deberta-v3-xsmall
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: unique-ape-807
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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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+ # unique-ape-807
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1850
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+ - Hamming Loss: 0.0497
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+ - Zero One Loss: 1.0
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+ - Jaccard Score: 1.0
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+ - Hamming Loss Optimised: 0.0497
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+ - Hamming Loss Threshold: 0.9000
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+ - Zero One Loss Optimised: 1.0
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+ - Zero One Loss Threshold: 0.9000
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+ - Jaccard Score Optimised: 1.0
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+ - Jaccard Score Threshold: 0.9000
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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: 5.0943791435964314e-05
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+ - train_batch_size: 20
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+ - eval_batch_size: 20
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+ - seed: 2024
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
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+ |:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
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+ | No log | 1.0 | 160 | 0.1872 | 0.0497 | 1.0 | 1.0 | 0.0497 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
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+ | No log | 2.0 | 320 | 0.1850 | 0.0497 | 1.0 | 1.0 | 0.0497 | 0.9000 | 1.0 | 0.9000 | 1.0 | 0.9000 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.5.1+cu118
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/deberta-v3-xsmall",
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+ "architectures": [
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+ "DebertaV2ForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 384,
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+ "id2label": {
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+ "0": "windows",
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+ "1": "python-2.7",
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+ "2": "pandas",
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+ "3": "multithreading",
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+ "4": "string",
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+ "5": "matplotlib",
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+ "6": "arrays",
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+ "7": "mysql",
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+ "8": "scipy",
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+ "9": "csv",
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+ "10": "django-models",
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+ "11": "numpy",
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+ "12": "google-app-engine",
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+ "21": "flask",
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+ "23": "sqlalchemy",
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+ },
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+ "initializer_range": 0.02,
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+ "string": 4,
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+ "tkinter": 20,
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+ "windows": 0
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+ },
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 6,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_dropout": 0,
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+ "pooler_hidden_act": "gelu",
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+ "pooler_hidden_size": 384,
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+ "pos_att_type": [
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+ "p2c",
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+ "c2p"
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+ ],
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+ "position_biased_input": false,
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+ "position_buckets": 256,
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+ "problem_type": "multi_label_classification",
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+ "relative_attention": true,
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+ "share_att_key": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.46.3",
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+ "type_vocab_size": 0,
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+ "vocab_size": 128100
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+ }
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