Model save

README.md

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+---
+library_name: peft
+tags:
+- trl
+- dpo
+- generated_from_trainer
+base_model: Weni/ZeroShot-3.3.34-Mistral-7b-Multilanguage-3.3.0-merged
+model-index:
+- name: ZeroShot-3.4.7-Mistral-7b-DPO-1.0.0
+  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. -->
+
+# ZeroShot-3.4.7-Mistral-7b-DPO-1.0.0
+
+This model is a fine-tuned version of [Weni/ZeroShot-3.3.34-Mistral-7b-Multilanguage-3.3.0-merged](https://huggingface.co/Weni/ZeroShot-3.3.34-Mistral-7b-Multilanguage-3.3.0-merged) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1629
+- Rewards/chosen: 0.4817
+- Rewards/rejected: -2.8132
+- Rewards/accuracies: 0.8977
+- Rewards/margins: 3.2949
+- Logps/rejected: -46.6655
+- Logps/chosen: -15.8817
+- Logits/rejected: -0.5753
+- Logits/chosen: -0.6695
+
+## 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: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 144
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.3185        | 1.02  | 50   | 0.2358          | 0.7735         | -2.1314          | 0.8864             | 2.9049          | -39.8482       | -12.9635     | -0.7282         | -0.8334       |
+| 0.2257        | 2.04  | 100  | 0.1629          | 0.4817         | -2.8132          | 0.8977             | 3.2949          | -46.6655       | -15.8817     | -0.5753         | -0.6695       |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.17.1
+- Tokenizers 0.15.2