End of training

README.md

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+---
+license: llama2
+base_model: meta-llama/Llama-2-7b-hf
+tags:
+- trl
+- dpo
+- generated_from_trainer
+library_name: peft
+model-index:
+- name: Llama-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V1
+  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_V1
+
+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: 1.2865
+- Rewards/chosen: -2.3072
+- Rewards/rejected: -1.8542
+- Rewards/accuracies: 0.5
+- Rewards/margins: -0.4531
+- Logps/rejected: -121.6291
+- Logps/chosen: -184.9154
+- Logits/rejected: 0.2000
+- Logits/chosen: 0.1668
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7102        | 0.3017 | 70   | 0.6900          | 0.0340         | 0.0258           | 0.7000             | 0.0082          | -102.8295      | -161.5030    | 0.6083          | 0.5744        |
+| 0.7024        | 0.6034 | 140  | 0.7276          | 0.0806         | 0.1382           | 0.3000             | -0.0575         | -101.7058      | -161.0370    | 0.6015          | 0.5681        |
+| 0.6653        | 0.9052 | 210  | 0.7362          | 0.0303         | 0.0739           | 0.4000             | -0.0435         | -102.3490      | -161.5399    | 0.6196          | 0.5858        |
+| 0.488         | 1.2069 | 280  | 0.8450          | -0.5919        | -0.4398          | 0.4000             | -0.1521         | -107.4859      | -167.7624    | 0.5482          | 0.5148        |
+| 0.5839        | 1.5086 | 350  | 0.8971          | -0.8481        | -0.6497          | 0.4000             | -0.1984         | -109.5843      | -170.3242    | 0.5183          | 0.4846        |
+| 0.503         | 1.8103 | 420  | 1.0273          | -1.1487        | -0.8225          | 0.4000             | -0.3262         | -111.3127      | -173.3304    | 0.4207          | 0.3883        |
+| 0.2083        | 2.1121 | 490  | 1.1693          | -1.6401        | -1.2436          | 0.4000             | -0.3965         | -115.5236      | -178.2447    | 0.2902          | 0.2576        |
+| 0.1395        | 2.4138 | 560  | 1.2310          | -2.1881        | -1.7991          | 0.6000             | -0.3890         | -121.0787      | -183.7240    | 0.2345          | 0.2015        |
+| 0.1618        | 2.7155 | 630  | 1.2865          | -2.3072        | -1.8542          | 0.5                | -0.4531         | -121.6291      | -184.9154    | 0.2000          | 0.1668        |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 3.2.0
+- Tokenizers 0.19.1