End of training

README.md

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+---
+license: mit
+base_model: microsoft/Phi-3-mini-4k-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: PHI30512HMAB20H
+  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. -->
+
+# PHI30512HMAB20H
+
+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: 0.0752
+
+## 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: 60
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.2937        | 0.09  | 10   | 0.8823          |
+| 0.4617        | 0.18  | 20   | 0.2708          |
+| 0.2681        | 0.27  | 30   | 2.7303          |
+| 0.9935        | 0.36  | 40   | 0.2454          |
+| 0.2512        | 0.45  | 50   | 0.2272          |
+| 0.2279        | 0.54  | 60   | 0.2115          |
+| 0.2067        | 0.63  | 70   | 0.2056          |
+| 0.2419        | 0.73  | 80   | 0.1810          |
+| 0.1545        | 0.82  | 90   | 0.0988          |
+| 0.0955        | 0.91  | 100  | 0.0863          |
+| 0.0846        | 1.0   | 110  | 0.0745          |
+| 0.073         | 1.09  | 120  | 0.0728          |
+| 0.0688        | 1.18  | 130  | 0.0799          |
+| 0.0731        | 1.27  | 140  | 0.0723          |
+| 0.0702        | 1.36  | 150  | 0.0740          |
+| 0.0793        | 1.45  | 160  | 0.0680          |
+| 0.0662        | 1.54  | 170  | 0.0651          |
+| 0.0666        | 1.63  | 180  | 0.0636          |
+| 0.0605        | 1.72  | 190  | 0.0640          |
+| 0.0678        | 1.81  | 200  | 0.0666          |
+| 0.0568        | 1.9   | 210  | 0.0702          |
+| 0.0568        | 1.99  | 220  | 0.0660          |
+| 0.0351        | 2.08  | 230  | 0.0769          |
+| 0.032         | 2.18  | 240  | 0.0946          |
+| 0.0288        | 2.27  | 250  | 0.0879          |
+| 0.0276        | 2.36  | 260  | 0.0766          |
+| 0.0316        | 2.45  | 270  | 0.0777          |
+| 0.0269        | 2.54  | 280  | 0.0781          |
+| 0.0265        | 2.63  | 290  | 0.0789          |
+| 0.0322        | 2.72  | 300  | 0.0770          |
+| 0.0362        | 2.81  | 310  | 0.0756          |
+| 0.0294        | 2.9   | 320  | 0.0749          |
+| 0.0277        | 2.99  | 330  | 0.0752          |
+
+
+### 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,
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+  "modules_to_save": null,
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+  "num_layers": 32,
+  "num_prefix_set": 3,
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+  "number_of_adapter_pre_layer": 8,
+  "ot_diversified_dispatcher": false,
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+  "peft_type": "PREFIX_MA_LORA",
+  "pool_selective_inference": true,
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+  "r": 8,
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+  "scale": 64,
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+  "simple_hidden_matching": true,
+  "simple_instance_matching": true,
+  "target_modules": [
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+  "task_type": "CAUSAL_LM",
+  "token_dim": 3072
+}

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added_tokens.json

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tokenizer_config.json

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