fine-tuning-Phi2-with-webglm-qa-with-lora_8

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: microsoft/phi-2
+model-index:
+- name: fine-tuning-Phi2-with-webglm-qa-with-lora_8
+  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. -->
+
+# fine-tuning-Phi2-with-webglm-qa-with-lora_8
+
+This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0935
+
+## 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: 5
+- total_train_batch_size: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 60
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 7.1823        | 0.31  | 20   | 6.1082          |
+| 4.0           | 0.63  | 40   | 0.9863          |
+| 0.7159        | 0.94  | 60   | 0.6293          |
+| 0.4994        | 1.26  | 80   | 0.4239          |
+| 0.3187        | 1.57  | 100  | 0.3044          |
+| 0.251         | 1.89  | 120  | 0.2567          |
+| 0.2189        | 2.2   | 140  | 0.2206          |
+| 0.1869        | 2.52  | 160  | 0.2000          |
+| 0.1741        | 2.83  | 180  | 0.1781          |
+| 0.1439        | 3.14  | 200  | 0.1638          |
+| 0.1543        | 3.46  | 220  | 0.1550          |
+| 0.1428        | 3.77  | 240  | 0.1455          |
+| 0.127         | 4.09  | 260  | 0.1394          |
+| 0.1206        | 4.4   | 280  | 0.1314          |
+| 0.1206        | 4.72  | 300  | 0.1298          |
+| 0.1162        | 5.03  | 320  | 0.1246          |
+| 0.109         | 5.35  | 340  | 0.1235          |
+| 0.1088        | 5.66  | 360  | 0.1190          |
+| 0.1062        | 5.97  | 380  | 0.1157          |
+| 0.0938        | 6.29  | 400  | 0.1146          |
+| 0.0945        | 6.6   | 420  | 0.1133          |
+| 0.1012        | 6.92  | 440  | 0.1105          |
+| 0.0881        | 7.23  | 460  | 0.1109          |
+| 0.0897        | 7.55  | 480  | 0.1091          |
+| 0.0837        | 7.86  | 500  | 0.1060          |
+| 0.0899        | 8.18  | 520  | 0.1051          |
+| 0.0803        | 8.49  | 540  | 0.1041          |
+| 0.0792        | 8.81  | 560  | 0.1021          |
+| 0.0885        | 9.12  | 580  | 0.1000          |
+| 0.0844        | 9.43  | 600  | 0.1004          |
+| 0.0704        | 9.75  | 620  | 0.0992          |
+| 0.0681        | 10.06 | 640  | 0.0994          |
+| 0.0727        | 10.38 | 660  | 0.0977          |
+| 0.0712        | 10.69 | 680  | 0.0970          |
+| 0.073         | 11.01 | 700  | 0.0971          |
+| 0.0683        | 11.32 | 720  | 0.0974          |
+| 0.0682        | 11.64 | 740  | 0.0964          |
+| 0.0716        | 11.95 | 760  | 0.0962          |
+| 0.0645        | 12.26 | 780  | 0.0948          |
+| 0.0662        | 12.58 | 800  | 0.0947          |
+| 0.0677        | 12.89 | 820  | 0.0947          |
+| 0.0626        | 13.21 | 840  | 0.0953          |
+| 0.0628        | 13.52 | 860  | 0.0946          |
+| 0.0642        | 13.84 | 880  | 0.0937          |
+| 0.0641        | 14.15 | 900  | 0.0939          |
+| 0.0587        | 14.47 | 920  | 0.0939          |
+| 0.0664        | 14.78 | 940  | 0.0933          |
+| 0.061         | 15.09 | 960  | 0.0931          |
+| 0.0596        | 15.41 | 980  | 0.0934          |
+| 0.0646        | 15.72 | 1000 | 0.0935          |
+
+
+### Framework versions
+
+- PEFT 0.7.1
+- Transformers 4.36.2
+- Pytorch 2.0.0
+- Datasets 2.15.0
+- Tokenizers 0.15.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/phi-2",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "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": [
+    "v_proj",
+    "k_proj",
+    "dense",
+    "fc1",
+    "fc2",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

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training_args.bin

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