End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: FairnessReciprocity_continuous
+  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. -->
+
+# FairnessReciprocity_continuous
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0238
+- Rmse: 0.1543
+- Mae: 0.1207
+- Corr: 0.2049
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rmse   | Mae    | Corr   |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
+| No log        | 1.0   | 250  | 0.0241          | 0.1554 | 0.1214 | 0.1927 |
+| 0.0361        | 2.0   | 500  | 0.0238          | 0.1543 | 0.1207 | 0.2049 |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0
+- Datasets 2.20.0
+- Tokenizers 0.19.1