amazon_helpfulness_classification_roberta_best_f1

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: amazon_helpfulness_classification_roberta_best_f1
+  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_roberta_best_f1
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4017
+- Accuracy: 0.8667
+- F1 Macro: 0.6891
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
+| 0.3249        | 1.0   | 7204  | 0.3543          | 0.869    | 0.5989   |
+| 0.3215        | 2.0   | 14408 | 0.3348          | 0.8652   | 0.5748   |
+| 0.3007        | 3.0   | 21612 | 0.3290          | 0.869    | 0.6384   |
+| 0.2813        | 4.0   | 28816 | 0.3628          | 0.8694   | 0.6689   |
+| 0.2382        | 5.0   | 36020 | 0.4117          | 0.8644   | 0.6922   |
+| 0.2046        | 6.0   | 43224 | 0.4769          | 0.8696   | 0.6675   |
+| 0.1724        | 7.0   | 50428 | 0.5750          | 0.8662   | 0.6691   |
+| 0.1457        | 8.0   | 57632 | 0.6255          | 0.8658   | 0.6783   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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