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stackoverflow_tag_classification/initial_run/bert-base-cased/unequaled-ape-267

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: unequaled-ape-267
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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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+ # unequaled-ape-267
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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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: 0.00010319797160518721
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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: 3
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.2
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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
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+ {
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+ "alpha_pattern": {},
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+ "base_model_class": "BertForSequenceClassification",
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+ "parent_library": "transformers.models.bert.modeling_bert"
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+ },
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+ "base_model_name_or_path": "google-bert/bert-base-cased",
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+ "bias": "none",
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+ "fan_in_fan_out": false,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layer_replication": null,
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+ "loftq_config": {},
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+ "lora_alpha": 20,
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+ "lora_dropout": 0,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 6,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "value",
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+ "query"
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+ ],
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+ "task_type": null,
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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