Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- trl
+- reward-trainer
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: deberta-v3-base-reward-model
+  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. -->
+
+# deberta-v3-base-reward-model
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0165
+- Accuracy: 0.995
+
+## 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: 1.41e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.039         | 2.0   | 100  | 0.0255          | 0.9925   |
+| 0.0092        | 4.0   | 200  | 0.0185          | 0.995    |
+| 0.0008        | 6.0   | 300  | 0.0148          | 0.995    |
+| 0.0022        | 8.0   | 400  | 0.0187          | 0.995    |
+| 0.0006        | 10.0  | 500  | 0.0165          | 0.995    |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.1
+- Datasets 3.0.1
+- Tokenizers 0.20.0