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bert_model_out

Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
Model card Files
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skkuprojectsh

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  1. README.md +68 -0
  2. config.json +56 -0
  3. model.safetensors +3 -0
  4. runs/Feb17_01-14-38_e1f984075007/events.out.tfevents.1739755470.e1f984075007.2230.0 +3 -0
  5. runs/Feb17_01-52-33_e1f984075007/events.out.tfevents.1739757170.e1f984075007.2230.1 +3 -0
  6. runs/Feb17_01-57-30_e1f984075007/events.out.tfevents.1739757488.e1f984075007.25391.0 +3 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: beomi/kcbert-base
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+ tags:
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+ - HHD
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+ - 10_class
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+ - multi_labels
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert_model_out
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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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+ # bert_model_out
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+
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+ This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the unsmile_data dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1440
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+ - Lrap: 0.8764
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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: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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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: 7
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Lrap |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 235 | 0.1493 | 0.8533 |
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+ | No log | 2.0 | 470 | 0.1293 | 0.8724 |
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+ | 0.1737 | 3.0 | 705 | 0.1241 | 0.8785 |
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+ | 0.1737 | 4.0 | 940 | 0.1310 | 0.8795 |
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+ | 0.0754 | 5.0 | 1175 | 0.1354 | 0.8778 |
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+ | 0.0754 | 6.0 | 1410 | 0.1425 | 0.8739 |
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+ | 0.0427 | 7.0 | 1645 | 0.1440 | 0.8764 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.0
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+ - Tokenizers 0.21.0
config.json ADDED
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+ {
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+ "_name_or_path": "beomi/kcbert-base",
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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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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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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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+ "9": "LABEL_9"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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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": 300,
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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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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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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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+ "transformers_version": "4.48.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30000
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+ }
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