fine-tuning-Phi2-with-webglm-qa-with-lora_6

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_6
+  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_6
+
+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: 0.1212
+
+## 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: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 7.3419        | 0.31  | 20   | 6.2616          |
+| 4.0421        | 0.63  | 40   | 0.8963          |
+| 0.6465        | 0.94  | 60   | 0.5726          |
+| 0.4575        | 1.26  | 80   | 0.3999          |
+| 0.309         | 1.57  | 100  | 0.3044          |
+| 0.2531        | 1.89  | 120  | 0.2605          |
+| 0.2235        | 2.2   | 140  | 0.2273          |
+| 0.1922        | 2.52  | 160  | 0.2091          |
+| 0.1793        | 2.83  | 180  | 0.1858          |
+| 0.1488        | 3.14  | 200  | 0.1734          |
+| 0.16          | 3.46  | 220  | 0.1646          |
+| 0.1497        | 3.77  | 240  | 0.1557          |
+| 0.1336        | 4.09  | 260  | 0.1489          |
+| 0.1278        | 4.4   | 280  | 0.1415          |
+| 0.1291        | 4.72  | 300  | 0.1392          |
+| 0.1244        | 5.03  | 320  | 0.1342          |
+| 0.1184        | 5.35  | 340  | 0.1319          |
+| 0.118         | 5.66  | 360  | 0.1289          |
+| 0.1153        | 5.97  | 380  | 0.1279          |
+| 0.1052        | 6.29  | 400  | 0.1250          |
+| 0.1058        | 6.6   | 420  | 0.1243          |
+| 0.1142        | 6.92  | 440  | 0.1226          |
+| 0.1026        | 7.23  | 460  | 0.1222          |
+| 0.1051        | 7.55  | 480  | 0.1214          |
+| 0.0977        | 7.86  | 500  | 0.1212          |
+
+
+### 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": [
+    "dense",
+    "k_proj",
+    "fc2",
+    "v_proj",
+    "fc1",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

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+size 94422368

training_args.bin

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