End of training

README.md

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+---
+base_model: microsoft/Phi-3-mini-4k-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: Phi0503HMA7
+  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. -->
+
+# Phi0503HMA7
+
+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: 0.0740
+
+## 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: 0.0003
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.7716        | 0.09  | 10   | 1.5978          |
+| 0.6746        | 0.18  | 20   | 0.3112          |
+| 0.2767        | 0.27  | 30   | 0.2928          |
+| 0.2464        | 0.36  | 40   | 0.2414          |
+| 0.2371        | 0.45  | 50   | 0.2208          |
+| 0.2186        | 0.54  | 60   | 0.1812          |
+| 0.1417        | 0.63  | 70   | 0.1198          |
+| 0.1133        | 0.73  | 80   | 0.0939          |
+| 0.0903        | 0.82  | 90   | 0.0932          |
+| 0.0878        | 0.91  | 100  | 0.0790          |
+| 0.0861        | 1.0   | 110  | 0.0991          |
+| 0.0751        | 1.09  | 120  | 0.0725          |
+| 0.108         | 1.18  | 130  | 0.0977          |
+| 0.0877        | 1.27  | 140  | 0.0792          |
+| 0.0675        | 1.36  | 150  | 0.0733          |
+| 0.0766        | 1.45  | 160  | 0.0715          |
+| 0.0681        | 1.54  | 170  | 0.0708          |
+| 0.0656        | 1.63  | 180  | 0.0665          |
+| 0.0578        | 1.72  | 190  | 0.0660          |
+| 0.0668        | 1.81  | 200  | 0.0655          |
+| 0.0551        | 1.9   | 210  | 0.0673          |
+| 0.0588        | 1.99  | 220  | 0.0670          |
+| 0.0376        | 2.08  | 230  | 0.0686          |
+| 0.0363        | 2.18  | 240  | 0.0813          |
+| 0.0292        | 2.27  | 250  | 0.0874          |
+| 0.0316        | 2.36  | 260  | 0.0777          |
+| 0.0352        | 2.45  | 270  | 0.0751          |
+| 0.0267        | 2.54  | 280  | 0.0772          |
+| 0.0284        | 2.63  | 290  | 0.0779          |
+| 0.0352        | 2.72  | 300  | 0.0759          |
+| 0.037         | 2.81  | 310  | 0.0748          |
+| 0.031         | 2.9   | 320  | 0.0740          |
+| 0.0313        | 2.99  | 330  | 0.0740          |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.0

adapter_config.json

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+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
+  "curr_learning": true,
+  "detached_training": true,
+  "dynamic_adapter_pool": true,
+  "enable_lora": null,
+  "encoder_hidden_size": 3072,
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+  "num_layers": 32,
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+  "ot_diversified_prefix": false,
+  "peft_type": "PREFIX_MA_LORA",
+  "pool_selective_inference": true,
+  "pool_selective_training": true,
+  "prefix_projection": true,
+  "r": 8,
+  "random_routing": false,
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+  "scale": 64,
+  "selective_num": 8,
+  "simple_hidden_matching": false,
+  "simple_instance_matching": true,
+  "target_modules": [
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+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "token_dim": 3072
+}

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added_tokens.json

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special_tokens_map.json

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tokenizer_config.json

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