End of training

README.md

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+---
+library_name: peft
+license: llama2
+base_model: meta-llama/Llama-2-7b-hf
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: Llama-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V2
+  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-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V2
+
+This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9352
+- Rewards/chosen: -1.7573
+- Rewards/rejected: -1.5576
+- Rewards/accuracies: 0.5
+- Rewards/margins: -0.1997
+- Logps/rejected: -110.7931
+- Logps/chosen: -134.9680
+- Logits/rejected: 0.0983
+- Logits/chosen: 0.0721
+
+## 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-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7029        | 0.3026 | 77   | 0.6933          | -0.0162        | -0.0163          | 0.3333             | 0.0001          | -95.3805       | -117.5575    | 0.5079          | 0.4933        |
+| 0.6605        | 0.6051 | 154  | 0.6804          | 0.0594         | 0.0318           | 0.6667             | 0.0276          | -94.8997       | -116.8017    | 0.4988          | 0.4837        |
+| 0.6291        | 0.9077 | 231  | 0.6684          | 0.2040         | 0.1302           | 0.75               | 0.0738          | -93.9156       | -115.3556    | 0.4931          | 0.4757        |
+| 0.3149        | 1.2102 | 308  | 0.6806          | -0.2081        | -0.3152          | 0.5833             | 0.1071          | -98.3691       | -119.4764    | 0.4810          | 0.4619        |
+| 0.3251        | 1.5128 | 385  | 0.7502          | -0.4333        | -0.4100          | 0.5833             | -0.0233         | -99.3170       | -121.7279    | 0.4258          | 0.4057        |
+| 0.2002        | 1.8153 | 462  | 0.8816          | -1.2398        | -1.0499          | 0.5                | -0.1899         | -105.7162      | -129.7932    | 0.3036          | 0.2813        |
+| 0.0182        | 2.1179 | 539  | 0.9166          | -1.4380        | -1.2371          | 0.5                | -0.2010         | -107.5881      | -131.7757    | 0.1946          | 0.1703        |
+| 0.2002        | 2.4204 | 616  | 0.9190          | -1.5677        | -1.4004          | 0.5                | -0.1673         | -109.2209      | -133.0719    | 0.1338          | 0.1085        |
+| 0.1982        | 2.7230 | 693  | 0.9352          | -1.7573        | -1.5576          | 0.5                | -0.1997         | -110.7931      | -134.9680    | 0.0983          | 0.0721        |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.45.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.2.0
+- Tokenizers 0.20.3