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-0_TTree1.4_TT0.9_TP0.7_TE0.2_V6
+  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_V6
+
+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: 0.9591
+- Rewards/chosen: -2.8498
+- Rewards/rejected: -3.2567
+- Rewards/accuracies: 0.6000
+- Rewards/margins: 0.4069
+- Logps/rejected: -145.1960
+- Logps/chosen: -111.9480
+- Logits/rejected: 0.1780
+- Logits/chosen: 0.1994
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6832        | 0.3007 | 69   | 0.6916          | -0.1597        | -0.1889          | 0.4000             | 0.0292          | -114.5179      | -85.0475     | 0.6233          | 0.6414        |
+| 0.7529        | 0.6013 | 138  | 0.6560          | -0.2047        | -0.3472          | 0.5                | 0.1425          | -116.1010      | -85.4976     | 0.6177          | 0.6354        |
+| 0.693         | 0.9020 | 207  | 0.6636          | 0.0291         | -0.0598          | 0.5                | 0.0889          | -113.2271      | -83.1593     | 0.6143          | 0.6331        |
+| 0.4049        | 1.2026 | 276  | 0.6820          | -0.9628        | -1.4793          | 0.5                | 0.5166          | -127.4224      | -93.0781     | 0.5148          | 0.5312        |
+| 0.3698        | 1.5033 | 345  | 0.6524          | -1.3282        | -1.9360          | 0.6000             | 0.6078          | -131.9892      | -96.7321     | 0.4151          | 0.4326        |
+| 0.3176        | 1.8039 | 414  | 0.7491          | -1.8527        | -2.3707          | 0.6000             | 0.5180          | -136.3361      | -101.9771    | 0.3469          | 0.3652        |
+| 0.361         | 2.1046 | 483  | 0.8110          | -2.2972        | -2.7632          | 0.5                | 0.4660          | -140.2609      | -106.4225    | 0.2734          | 0.2932        |
+| 0.3286        | 2.4052 | 552  | 0.9465          | -2.7604        | -3.1816          | 0.6000             | 0.4212          | -144.4454      | -111.0542    | 0.1886          | 0.2099        |
+| 0.0545        | 2.7059 | 621  | 0.9591          | -2.8498        | -3.2567          | 0.6000             | 0.4069          | -145.1960      | -111.9480    | 0.1780          | 0.1994        |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1