edumunozsala/phi3-mini-adapter-ql-py-code

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: microsoft/Phi-3-mini-4k-instruct
+model-index:
+- name: phi-3-mini-QLoRA
+  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. -->
+
+# phi-3-mini-QLoRA
+
+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: 0.5741
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.1422        | 0.1810 | 100  | 0.6625          |
+| 0.6238        | 0.3619 | 200  | 0.6002          |
+| 0.5932        | 0.5429 | 300  | 0.5906          |
+| 0.5926        | 0.7238 | 400  | 0.5860          |
+| 0.5794        | 0.9048 | 500  | 0.5834          |
+| 0.5868        | 1.0857 | 600  | 0.5815          |
+| 0.5711        | 1.2667 | 700  | 0.5796          |
+| 0.5729        | 1.4476 | 800  | 0.5785          |
+| 0.5858        | 1.6286 | 900  | 0.5772          |
+| 0.5732        | 1.8095 | 1000 | 0.5763          |
+| 0.5736        | 1.9905 | 1100 | 0.5756          |
+| 0.5638        | 2.1715 | 1200 | 0.5754          |
+| 0.5769        | 2.3524 | 1300 | 0.5746          |
+| 0.5668        | 2.5334 | 1400 | 0.5745          |
+| 0.5675        | 2.7143 | 1500 | 0.5742          |
+| 0.5693        | 2.8953 | 1600 | 0.5741          |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "gate_proj",
+    "q_proj",
+    "up_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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added_tokens.json

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special_tokens_map.json

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+}

tokenizer.model

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tokenizer_config.json

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+  "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
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+  "model_max_length": 4096,
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+  "sp_model_kwargs": {},
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+}

training_args.bin

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