Model save

README.md

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+---
+base_model: microsoft/Phi-3-mini-4k-instruct
+library_name: peft
+license: mit
+tags:
+- trl
+- orpo
+- generated_from_trainer
+model-index:
+- name: ORPO-PHI-3
+  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. -->
+
+# ORPO-PHI-3
+
+This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7712
+- Rewards/chosen: -0.1577
+- Rewards/rejected: -0.1527
+- Rewards/accuracies: 0.3000
+- Rewards/margins: -0.0050
+- Logps/rejected: -1.5273
+- Logps/chosen: -1.5771
+- Logits/rejected: 2.7883
+- Logits/chosen: 1.8098
+- Nll Loss: 1.6979
+- Log Odds Ratio: -0.7331
+- Log Odds Chosen: -0.0576
+
+## 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: 8e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
+| 1.7534        | 0.2020 | 25   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
+| 1.9166        | 0.4040 | 50   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
+| 1.436         | 0.6061 | 75   | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
+| 1.6618        | 0.8081 | 100  | 1.7712          | -0.1577        | -0.1527          | 0.3000             | -0.0050         | -1.5273        | -1.5771      | 2.7883          | 1.8098        | 1.6979   | -0.7331        | -0.0576         |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

adapter_config.json

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+{
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+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_up_proj",
+    "down_proj",
+    "o_proj",
+    "qkv_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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added_tokens.json

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runs/Jul01_08-16-25_6d9398927960/events.out.tfevents.1719821787.6d9398927960.2537.0

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special_tokens_map.json

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tokenizer_config.json

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+}

training_args.bin

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