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MaggieZhang/lora_bert_classification

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ base_model: bert-base-cased
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+ model-index:
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+ - name: test_trainer
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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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+ # test_trainer
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+
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+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3803
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+ - Accuracy: 0.842
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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: 5e-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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+ - 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: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 125 | 0.6786 | 0.608 |
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+ | No log | 2.0 | 250 | 0.6718 | 0.598 |
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+ | No log | 3.0 | 375 | 0.6695 | 0.574 |
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+ | 0.6888 | 4.0 | 500 | 0.6583 | 0.599 |
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+ | 0.6888 | 5.0 | 625 | 0.6262 | 0.684 |
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+ | 0.6888 | 6.0 | 750 | 0.5936 | 0.697 |
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+ | 0.6888 | 7.0 | 875 | 0.5520 | 0.721 |
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+ | 0.6057 | 8.0 | 1000 | 0.5149 | 0.746 |
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+ | 0.6057 | 9.0 | 1125 | 0.4848 | 0.762 |
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+ | 0.6057 | 10.0 | 1250 | 0.4558 | 0.779 |
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+ | 0.6057 | 11.0 | 1375 | 0.4346 | 0.793 |
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+ | 0.4583 | 12.0 | 1500 | 0.4215 | 0.801 |
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+ | 0.4583 | 13.0 | 1625 | 0.4094 | 0.815 |
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+ | 0.4583 | 14.0 | 1750 | 0.4027 | 0.816 |
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+ | 0.4583 | 15.0 | 1875 | 0.3962 | 0.82 |
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+ | 0.3847 | 16.0 | 2000 | 0.3926 | 0.823 |
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+ | 0.3847 | 17.0 | 2125 | 0.3873 | 0.835 |
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+ | 0.3847 | 18.0 | 2250 | 0.3857 | 0.833 |
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+ | 0.3847 | 19.0 | 2375 | 0.3823 | 0.836 |
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+ | 0.3565 | 20.0 | 2500 | 0.3819 | 0.837 |
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+ | 0.3565 | 21.0 | 2625 | 0.3850 | 0.837 |
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+ | 0.3565 | 22.0 | 2750 | 0.3806 | 0.839 |
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+ | 0.3565 | 23.0 | 2875 | 0.3801 | 0.84 |
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+ | 0.3348 | 24.0 | 3000 | 0.3808 | 0.842 |
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+ | 0.3348 | 25.0 | 3125 | 0.3803 | 0.842 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.8.2
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.1
adapter_config.json ADDED
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+ {
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+ "alpha_pattern": {},
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+ "base_model_name_or_path": "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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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 1,
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+ "lora_dropout": 0.1,
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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": 1,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "query",
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+ "value"
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+ ],
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+ "task_type": "SEQ_CLS",
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+ "use_rslora": false
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+ }
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