add lora file

README.md

@@ -1,3 +1,80 @@
 ---
-license: mit
+license: other
+base_model: microsoft/phi-2
+tags:
+- alignment-handbook
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/ultrachat_200k
+model-index:
+- name: phi-sft-lora
+  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-sft-lora
+
+This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the HuggingFaceH4/ultrachat_200k dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2210
+
+## 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: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss |
+|:-------------:|:-----:|:------:|:---------------:|
+| 1.1971        | 0.05  | 10000  | 1.2409          |
+| 1.1911        | 0.1   | 20000  | 1.2349          |
+| 1.4103        | 0.14  | 30000  | 1.2317          |
+| 1.192         | 0.19  | 40000  | 1.2295          |
+| 1.4831        | 0.24  | 50000  | 1.2275          |
+| 1.2857        | 0.29  | 60000  | 1.2266          |
+| 1.014         | 0.34  | 70000  | 1.2256          |
+| 1.2777        | 0.38  | 80000  | 1.2251          |
+| 0.9019        | 0.43  | 90000  | 1.2241          |
+| 1.1926        | 0.48  | 100000 | 1.2235          |
+| 1.2298        | 0.53  | 110000 | 1.2233          |
+| 1.1102        | 0.58  | 120000 | 1.2228          |
+| 1.3166        | 0.63  | 130000 | 1.2219          |
+| 1.1452        | 0.67  | 140000 | 1.2217          |
+| 1.308         | 0.72  | 150000 | 1.2217          |
+| 0.9096        | 0.77  | 160000 | 1.2215          |
+| 1.2817        | 0.82  | 170000 | 1.2211          |
+| 1.2904        | 0.87  | 180000 | 1.2211          |
+| 0.9066        | 0.91  | 190000 | 1.2210          |
+| 1.1807        | 0.96  | 200000 | 1.2210          |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.1+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

adapter_config.json

@@ -0,0 +1,23 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/phi-2",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 8,
+  "lora_dropout": 0.1,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "out_proj",
+    "Wqkv"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

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added_tokens.json

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+}

all_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 1.2209750413894653,
+    "eval_runtime": 6471.7309,
+    "eval_samples": 23110,
+    "eval_samples_per_second": 3.571,
+    "eval_steps_per_second": 1.785,
+    "train_loss": 1.2418477715456762,
+    "train_runtime": 258582.6373,
+    "train_samples": 207865,
+    "train_samples_per_second": 0.804,
+    "train_steps_per_second": 0.804
+}

config.json

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+{
+  "_name_or_path": "microsoft/phi-2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "PhiForCausalLM"
+  ],
+  "attn_pdrop": 0.0,
+  "auto_map": {
+    "AutoConfig": "microsoft/phi-2--configuration_phi.PhiConfig",
+    "AutoModelForCausalLM": "microsoft/phi-2--modeling_phi.PhiForCausalLM"
+  },
+  "embd_pdrop": 0.0,
+  "flash_attn": false,
+  "flash_rotary": false,
+  "fused_dense": false,
+  "img_processor": null,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "phi-msft",
+  "n_embd": 2560,
+  "n_head": 32,
+  "n_head_kv": null,
+  "n_inner": null,
+  "n_layer": 32,
+  "n_positions": 2048,
+  "quantization_config": {
+    "bnb_4bit_compute_dtype": "float16",
+    "bnb_4bit_quant_type": "nf4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": true,
+    "load_in_8bit": false,
+    "quant_method": "bitsandbytes"
+  },
+  "resid_pdrop": 0.1,
+  "rotary_dim": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.0",
+  "use_cache": true,
+  "vocab_size": 51200
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 1.2209750413894653,
+    "eval_runtime": 6471.7309,
+    "eval_samples": 23110,
+    "eval_samples_per_second": 3.571,
+    "eval_steps_per_second": 1.785
+}

runs/Dec17_21-41-42_delab-42QWE/events.out.tfevents.1702816912.delab-42QWE.14096.0

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runs/Dec17_21-41-42_delab-42QWE/events.out.tfevents.1703081967.delab-42QWE.14096.1

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special_tokens_map.json

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tokenizer_config.json

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+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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+}

train_results.json

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+}

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