amazon_helpfulness_classification_dapt_tap

README.md

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+---
+license: mit
+base_model: BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: amazon_helpfulness_classification_dapt_tap
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# amazon_helpfulness_classification_dapt_tap
+
+This model is a fine-tuned version of [BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model](https://huggingface.co/BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3428
+- Accuracy: 0.8785
+- F1 Macro: 0.6863
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
+| 0.315         | 1.0   | 7204  | 0.3045          | 0.874    | 0.6410   |
+| 0.3083        | 2.0   | 14408 | 0.3373          | 0.8722   | 0.6349   |
+| 0.2639        | 3.0   | 21612 | 0.3507          | 0.8768   | 0.6922   |
+| 0.2388        | 4.0   | 28816 | 0.4179          | 0.87     | 0.6659   |
+| 0.1534        | 5.0   | 36020 | 0.5956          | 0.8738   | 0.6830   |
+| 0.1524        | 6.0   | 43224 | 0.6679          | 0.8684   | 0.6796   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

model.safetensors

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