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: Phi0503B1
+  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. -->
+
+# Phi0503B1
+
+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: 0.0800
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|
+| 3.5697        | 0.09  | 10   | 0.7185          |
+| 0.345         | 0.18  | 20   | 0.1655          |
+| 0.1552        | 0.27  | 30   | 0.1343          |
+| 0.1345        | 0.36  | 40   | 0.1175          |
+| 0.121         | 0.45  | 50   | 0.1152          |
+| 0.1088        | 0.54  | 60   | 0.0861          |
+| 0.0923        | 0.63  | 70   | 0.0942          |
+| 0.0773        | 0.73  | 80   | 0.0681          |
+| 0.0606        | 0.82  | 90   | 0.0686          |
+| 0.0647        | 0.91  | 100  | 0.0624          |
+| 0.062         | 1.0   | 110  | 0.0663          |
+| 0.0434        | 1.09  | 120  | 0.0687          |
+| 0.042         | 1.18  | 130  | 0.0675          |
+| 0.0503        | 1.27  | 140  | 0.0681          |
+| 0.0445        | 1.36  | 150  | 0.0654          |
+| 0.0511        | 1.45  | 160  | 0.0593          |
+| 0.0462        | 1.54  | 170  | 0.0687          |
+| 0.0498        | 1.63  | 180  | 0.0651          |
+| 0.0448        | 1.72  | 190  | 0.0640          |
+| 0.043         | 1.81  | 200  | 0.0636          |
+| 0.04          | 1.9   | 210  | 0.0617          |
+| 0.043         | 1.99  | 220  | 0.0613          |
+| 0.0226        | 2.08  | 230  | 0.0657          |
+| 0.0165        | 2.18  | 240  | 0.0788          |
+| 0.011         | 2.27  | 250  | 0.0943          |
+| 0.0097        | 2.36  | 260  | 0.0946          |
+| 0.0167        | 2.45  | 270  | 0.0864          |
+| 0.0105        | 2.54  | 280  | 0.0827          |
+| 0.0118        | 2.63  | 290  | 0.0819          |
+| 0.0156        | 2.72  | 300  | 0.0802          |
+| 0.0137        | 2.81  | 310  | 0.0800          |
+| 0.013         | 2.9   | 320  | 0.0800          |
+| 0.0098        | 2.99  | 330  | 0.0800          |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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,
+  "peft_type": "LORA",
+  "r": 16,
+  "target_modules": [
+    "qkv_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.bin

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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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