Model save

README.md

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+---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- trl
+- dpo
+- llama-factory
+- generated_from_trainer
+model-index:
+- name: Llama-3.1-8B-Instruct_dpo_sg_values_p025_OA_gold
+  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. -->
+
+# Llama-3.1-8B-Instruct_dpo_sg_values_p025_OA_gold
+
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1398
+- Rewards/chosen: -0.3263
+- Rewards/rejected: -3.7101
+- Rewards/accuracies: 0.9340
+- Rewards/margins: 3.3838
+- Logps/chosen: -5.3544
+- Logps/rejected: -43.7234
+- Logits/chosen: -0.8241
+- Logits/rejected: -0.8535
+
+## 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: 1e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
+| 0.677         | 0.1495 | 250  | 0.6611          | -0.0030        | -0.0688          | 0.8780             | 0.0658          | -2.1210      | -7.3104        | -0.6673       | -0.6792         |
+| 0.4141        | 0.2990 | 500  | 0.3328          | -0.1370        | -1.2934          | 0.8960             | 1.1564          | -3.4617      | -19.5564       | -0.7405       | -0.7604         |
+| 0.1869        | 0.4486 | 750  | 0.1943          | -0.3266        | -2.7983          | 0.9280             | 2.4718          | -5.3572      | -34.6058       | -0.8272       | -0.8525         |
+| 0.1234        | 0.5981 | 1000 | 0.1579          | -0.3430        | -3.2984          | 0.9380             | 2.9554          | -5.5213      | -39.6065       | -0.8336       | -0.8610         |
+| 0.122         | 0.7476 | 1250 | 0.1439          | -0.3187        | -3.5609          | 0.9360             | 3.2422          | -5.2784      | -42.2310       | -0.8265       | -0.8553         |
+| 0.0821        | 0.8971 | 1500 | 0.1398          | -0.3263        | -3.7101          | 0.9340             | 3.3838          | -5.3544      | -43.7234       | -0.8241       | -0.8535         |
+
+
+### Framework versions
+
+- PEFT 0.15.2
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 2.21.0
+- Tokenizers 0.21.1