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-0_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-0_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: 0.4540
+- Rewards/chosen: -1.9538
+- Rewards/rejected: -2.8279
+- Rewards/accuracies: 0.9000
+- Rewards/margins: 0.8741
+- Logps/rejected: -178.4166
+- Logps/chosen: -140.8054
+- Logits/rejected: -0.0659
+- Logits/chosen: -0.0598
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6759        | 0.3023 | 60   | 0.6970          | 0.0373         | 0.0397           | 0.6000             | -0.0024         | -149.7405      | -120.8940    | 0.4429          | 0.4532        |
+| 0.6811        | 0.6045 | 120  | 0.6723          | -0.0412        | -0.0677          | 0.5                | 0.0265          | -150.8149      | -121.6795    | 0.4688          | 0.4793        |
+| 0.5824        | 0.9068 | 180  | 0.6747          | 0.0390         | -0.0060          | 0.8000             | 0.0450          | -150.1981      | -120.8773    | 0.4537          | 0.4631        |
+| 0.3049        | 1.2091 | 240  | 0.5606          | -0.3769        | -0.6960          | 0.7000             | 0.3191          | -157.0981      | -125.0365    | 0.3873          | 0.3966        |
+| 0.3915        | 1.5113 | 300  | 0.5289          | -0.4550        | -0.8493          | 0.9000             | 0.3943          | -158.6304      | -125.8171    | 0.3314          | 0.3395        |
+| 0.476         | 1.8136 | 360  | 0.5109          | -0.7144        | -1.1970          | 0.9000             | 0.4826          | -162.1081      | -128.4113    | 0.2160          | 0.2235        |
+| 0.1137        | 2.1159 | 420  | 0.5121          | -1.1098        | -1.6334          | 0.8000             | 0.5236          | -166.4716      | -132.3654    | 0.0934          | 0.1001        |
+| 0.3063        | 2.4181 | 480  | 0.4482          | -1.9206        | -2.8102          | 0.9000             | 0.8895          | -178.2394      | -140.4735    | -0.0433         | -0.0370       |
+| 0.2409        | 2.7204 | 540  | 0.4540          | -1.9538        | -2.8279          | 0.9000             | 0.8741          | -178.4166      | -140.8054    | -0.0659         | -0.0598       |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.45.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.2.0
+- Tokenizers 0.20.3