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: Phi0511B2
+  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. -->
+
+# Phi0511B2
+
+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: 0.0718
+
+## 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: 80
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 5.4836        | 0.09  | 10   | 5.4324          |
+| 5.4542        | 0.18  | 20   | 5.2447          |
+| 4.9491        | 0.27  | 30   | 4.1820          |
+| 3.3816        | 0.36  | 40   | 2.1650          |
+| 1.3373        | 0.45  | 50   | 0.5823          |
+| 0.4096        | 0.54  | 60   | 0.1966          |
+| 0.1569        | 0.63  | 70   | 0.1428          |
+| 0.1378        | 0.73  | 80   | 0.1266          |
+| 0.1135        | 0.82  | 90   | 0.1250          |
+| 0.127         | 0.91  | 100  | 0.1191          |
+| 0.1078        | 1.0   | 110  | 0.1075          |
+| 0.0958        | 1.09  | 120  | 0.0948          |
+| 0.0877        | 1.18  | 130  | 0.0946          |
+| 0.0995        | 1.27  | 140  | 0.0841          |
+| 0.0822        | 1.36  | 150  | 0.1001          |
+| 0.0901        | 1.45  | 160  | 0.0814          |
+| 0.0754        | 1.54  | 170  | 0.0833          |
+| 0.0806        | 1.63  | 180  | 0.1000          |
+| 0.0763        | 1.72  | 190  | 0.0800          |
+| 0.0787        | 1.81  | 200  | 0.0787          |
+| 0.0637        | 1.9   | 210  | 0.0753          |
+| 0.0657        | 1.99  | 220  | 0.0799          |
+| 0.0605        | 2.08  | 230  | 0.0777          |
+| 0.0625        | 2.18  | 240  | 0.0740          |
+| 0.0544        | 2.27  | 250  | 0.0743          |
+| 0.0572        | 2.36  | 260  | 0.0736          |
+| 0.0593        | 2.45  | 270  | 0.0739          |
+| 0.0575        | 2.54  | 280  | 0.0729          |
+| 0.0584        | 2.63  | 290  | 0.0737          |
+| 0.057         | 2.72  | 300  | 0.0728          |
+| 0.0622        | 2.81  | 310  | 0.0720          |
+| 0.0566        | 2.9   | 320  | 0.0718          |
+| 0.0594        | 2.99  | 330  | 0.0718          |
+
+
+### 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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+{
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+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
+  "enable_lora": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "merge_weights": false,
+  "modules_to_save": null,
+  "number_of_adapter_pre_layer": 8,
+  "peft_type": "M_LORA",
+  "r": 8,
+  "target_modules": [
+    "qkv_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

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special_tokens_map.json

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tokenizer_config.json

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