Model save

README.md

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+---
+library_name: peft
+tags:
+- trl
+- dpo
+- DPO
+- WeniGPT
+- generated_from_trainer
+base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
+model-index:
+- name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO
+  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. -->
+
+# WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO
+
+This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2005
+- Rewards/chosen: 1.7621
+- Rewards/rejected: -0.7248
+- Rewards/accuracies: 1.0
+- Rewards/margins: 2.4869
+- Logps/rejected: -271.5133
+- Logps/chosen: -102.9727
+- Logits/rejected: -1.8958
+- Logits/chosen: -1.8013
+
+## 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: 5e-06
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- total_eval_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.03
+- training_steps: 180
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5477        | 0.97  | 30   | 0.4843          | 0.4718         | -0.1109          | 0.8571             | 0.5827          | -269.4668      | -107.2735    | -1.8863         | -1.7949       |
+| 0.3542        | 1.94  | 60   | 0.3440          | 0.9609         | -0.2516          | 1.0                | 1.2125          | -269.9360      | -105.6431    | -1.8903         | -1.7979       |
+| 0.2892        | 2.9   | 90   | 0.2756          | 1.3199         | -0.4182          | 1.0                | 1.7381          | -270.4914      | -104.4467    | -1.8928         | -1.7995       |
+| 0.1858        | 3.87  | 120  | 0.2327          | 1.6010         | -0.5696          | 1.0                | 2.1706          | -270.9958      | -103.5094    | -1.8947         | -1.8008       |
+| 0.1811        | 4.84  | 150  | 0.2076          | 1.7245         | -0.6925          | 1.0                | 2.4170          | -271.4054      | -103.0979    | -1.8954         | -1.8010       |
+| 0.2065        | 5.81  | 180  | 0.2005          | 1.7621         | -0.7248          | 1.0                | 2.4869          | -271.5133      | -102.9727    | -1.8958         | -1.8013       |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.18.0
+- Tokenizers 0.15.2