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_TTree1.4_TT0.9_TP0.7_TE0.2_V7
+  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_TTree1.4_TT0.9_TP0.7_TE0.2_V7
+
+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: 0.7581
+- Rewards/chosen: -1.7006
+- Rewards/rejected: -1.8759
+- Rewards/accuracies: 0.6000
+- Rewards/margins: 0.1753
+- Logps/rejected: -131.1391
+- Logps/chosen: -96.3973
+- Logits/rejected: -0.0046
+- Logits/chosen: 0.0503
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7096        | 0.3004 | 67   | 0.6970          | -0.0217        | -0.0183          | 0.5                | -0.0034         | -112.5630      | -79.6082     | 0.6024          | 0.6487        |
+| 0.6684        | 0.6009 | 134  | 0.6829          | -0.0429        | -0.0704          | 0.8000             | 0.0275          | -113.0842      | -79.8203     | 0.5780          | 0.6246        |
+| 0.7283        | 0.9013 | 201  | 0.6982          | 0.0550         | 0.0616           | 0.6000             | -0.0067         | -111.7634      | -78.8413     | 0.5848          | 0.6319        |
+| 0.2339        | 1.2018 | 268  | 0.6630          | -0.1631        | -0.2504          | 0.7000             | 0.0873          | -114.8840      | -81.0225     | 0.4681          | 0.5163        |
+| 0.3526        | 1.5022 | 335  | 0.6523          | -0.5545        | -0.6837          | 0.6000             | 0.1292          | -119.2165      | -84.9362     | 0.3518          | 0.4006        |
+| 0.2787        | 1.8027 | 402  | 0.6181          | -0.4772        | -0.6749          | 0.6000             | 0.1977          | -119.1291      | -84.1633     | 0.3107          | 0.3615        |
+| 0.2577        | 2.1031 | 469  | 0.6856          | -1.0419        | -1.1941          | 0.5                | 0.1522          | -124.3209      | -89.8106     | 0.1666          | 0.2190        |
+| 0.0942        | 2.4036 | 536  | 0.7344          | -1.5330        | -1.7182          | 0.6000             | 0.1852          | -129.5615      | -94.7212     | 0.0278          | 0.0822        |
+| 0.0952        | 2.7040 | 603  | 0.7581          | -1.7006        | -1.8759          | 0.6000             | 0.1753          | -131.1391      | -96.3973     | -0.0046         | 0.0503        |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.45.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.2.0
+- Tokenizers 0.20.3