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: PHI30512HMAB18H
+  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. -->
+
+# PHI30512HMAB18H
+
+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: 60
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.2497        | 0.09  | 10   | 0.9067          |
+| 0.4537        | 0.18  | 20   | 0.2641          |
+| 0.3338        | 0.27  | 30   | 0.2501          |
+| 0.2554        | 0.36  | 40   | 0.2343          |
+| 0.2601        | 0.45  | 50   | 0.2149          |
+| 0.2187        | 0.54  | 60   | 0.2108          |
+| 0.2111        | 0.63  | 70   | 0.2032          |
+| 0.1904        | 0.73  | 80   | 0.1720          |
+| 0.1685        | 0.82  | 90   | 0.1673          |
+| 0.1626        | 0.91  | 100  | 0.1636          |
+| 0.1578        | 1.0   | 110  | 0.1104          |
+| 0.1041        | 1.09  | 120  | 0.0870          |
+| 0.0882        | 1.18  | 130  | 0.0854          |
+| 0.0933        | 1.27  | 140  | 0.0801          |
+| 0.0816        | 1.36  | 150  | 0.0792          |
+| 0.0829        | 1.45  | 160  | 0.0751          |
+| 0.0741        | 1.54  | 170  | 0.0777          |
+| 0.0773        | 1.63  | 180  | 0.0732          |
+| 0.0705        | 1.72  | 190  | 0.0705          |
+| 0.0749        | 1.81  | 200  | 0.0677          |
+| 0.0624        | 1.9   | 210  | 0.0734          |
+| 0.0655        | 1.99  | 220  | 0.0722          |
+| 0.0436        | 2.08  | 230  | 0.0802          |
+| 0.0464        | 2.18  | 240  | 0.0876          |
+| 0.0402        | 2.27  | 250  | 0.0758          |
+| 0.0379        | 2.36  | 260  | 0.0742          |
+| 0.0435        | 2.45  | 270  | 0.0732          |
+| 0.0348        | 2.54  | 280  | 0.0766          |
+| 0.0356        | 2.63  | 290  | 0.0775          |
+| 0.0409        | 2.72  | 300  | 0.0757          |
+| 0.0473        | 2.81  | 310  | 0.0746          |
+| 0.0401        | 2.9   | 320  | 0.0741          |
+| 0.0402        | 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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+  "adaptive_ratio_decay": 1.005,
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+  "allow_empty_lora": false,
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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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+  "lora_dropout": 0.05,
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+  "modules_to_save": null,
+  "num_attention_heads": 32,
+  "num_layers": 32,
+  "num_prefix_set": 3,
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+  "number_of_adapter_pre_layer": 8,
+  "ot_diversified_dispatcher": false,
+  "ot_diversified_prefix": false,
+  "peft_type": "PREFIX_MA_LORA",
+  "pool_selective_inference": true,
+  "pool_selective_training": 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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special_tokens_map.json

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