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tapt_helpfulness_base_pretraining_model_full_train

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: tapt_helpfulness_base_pretraining_model_full_train
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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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+ # tapt_helpfulness_base_pretraining_model_full_train
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2718
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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: 0.0001
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+ - train_batch_size: 21
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+ - eval_batch_size: 21
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 42
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+ - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 1.6862 | 1.0 | 1068 | 1.5262 |
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+ | 1.5864 | 2.0 | 2137 | 1.4706 |
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+ | 1.5423 | 3.0 | 3205 | 1.4346 |
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+ | 1.5058 | 4.0 | 4274 | 1.4223 |
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+ | 1.4792 | 5.0 | 5342 | 1.4100 |
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+ | 1.4549 | 6.0 | 6411 | 1.3948 |
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+ | 1.435 | 7.0 | 7479 | 1.3851 |
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+ | 1.4148 | 8.0 | 8548 | 1.3749 |
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+ | 1.3968 | 9.0 | 9616 | 1.3567 |
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+ | 1.3806 | 10.0 | 10685 | 1.3548 |
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+ | 1.3662 | 11.0 | 11753 | 1.3347 |
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+ | 1.3495 | 12.0 | 12822 | 1.3369 |
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+ | 1.3382 | 13.0 | 13890 | 1.3232 |
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+ | 1.3238 | 14.0 | 14959 | 1.3231 |
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+ | 1.3138 | 15.0 | 16027 | 1.3157 |
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+ | 1.2983 | 16.0 | 17096 | 1.3012 |
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+ | 1.2916 | 17.0 | 18164 | 1.2871 |
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+ | 1.282 | 18.0 | 19233 | 1.2919 |
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+ | 1.2738 | 19.0 | 20301 | 1.2825 |
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+ | 1.267 | 19.99 | 21360 | 1.2842 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.15.2
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