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README.md

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+---
+library_name: peft
+license: other
+base_model: microsoft/Phi-3-mini-4k-instruct
+tags:
+- llama-factory
+- lora
+- generated_from_trainer
+model-index:
+- name: lora
+  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. -->
+
+# lora
+
+This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the flock_task4_tranning dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1386
+
+## 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: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- total_eval_batch_size: 2
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.047         | 0.0501 | 50   | 1.2594          |
+| 1.027         | 0.1002 | 100  | 1.2322          |
+| 0.916         | 0.1502 | 150  | 1.2325          |
+| 0.995         | 0.2003 | 200  | 1.2030          |
+| 0.981         | 0.2504 | 250  | 1.1924          |
+| 0.9663        | 0.3005 | 300  | 1.1807          |
+| 0.8533        | 0.3505 | 350  | 1.1778          |
+| 0.9052        | 0.4006 | 400  | 1.1744          |
+| 0.9526        | 0.4507 | 450  | 1.1691          |
+| 0.8949        | 0.5008 | 500  | 1.1603          |
+| 0.8881        | 0.5508 | 550  | 1.1526          |
+| 0.9001        | 0.6009 | 600  | 1.1503          |
+| 0.8708        | 0.6510 | 650  | 1.1502          |
+| 0.8791        | 0.7011 | 700  | 1.1403          |
+| 0.9239        | 0.7511 | 750  | 1.1463          |
+| 0.8726        | 0.8012 | 800  | 1.1400          |
+| 0.8509        | 0.8513 | 850  | 1.1403          |
+| 0.8615        | 0.9014 | 900  | 1.1386          |
+| 0.9553        | 0.9514 | 950  | 1.1384          |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.48.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "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": 256,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_up_proj",
+    "o_proj",
+    "qkv_proj",
+    "down_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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special_tokens_map.json

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+}

tokenizer.model

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tokenizer_config.json

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+}

training_args.bin

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