Add personality LLM culture model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,202 @@
+---
+base_model: meta-llama/Llama-2-7b-chat-hf
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
+  "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": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "qa_outputs"
+  ],
+  "peft_type": "LORA",
+  "r": 4,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "q_proj"
+  ],
+  "task_type": "QUESTION_ANS",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aca92d99c8f959106d6671d4fe0d5d73dad7e39fa3d3c5b20c29b972d34c4481
+size 1057015264

added_tokens.json

@@ -0,0 +1,3 @@
+{
+  "<pad>": 32000
+}

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4873d19dbf794851be757b9b2c2bc67364d77a10d9fbce8b78f3ff96d7c438af
+size 16884858

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c880939357c18a86a96088459b1eb6b034caaadb330aba305e407f167c1b7f8
+size 1064

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a7dc4aac7955c9bd5f5351b4a4b9356e4ea665f95208b11d52496da04f5e7cb2
+size 3619355

tokenizer_config.json

@@ -0,0 +1,51 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

trainer_state.json

@@ -0,0 +1,453 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.4166666666666667,
+  "eval_steps": 5,
+  "global_step": 50,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.008333333333333333,
+      "grad_norm": 2.3885583877563477,
+      "learning_rate": 0.001,
+      "loss": 5.2644,
+      "step": 1
+    },
+    {
+      "epoch": 0.016666666666666666,
+      "grad_norm": 3.1313512325286865,
+      "learning_rate": 0.001,
+      "loss": 4.4436,
+      "step": 2
+    },
+    {
+      "epoch": 0.025,
+      "grad_norm": NaN,
+      "learning_rate": 0.001,
+      "loss": 4.1142,
+      "step": 3
+    },
+    {
+      "epoch": 0.03333333333333333,
+      "grad_norm": 2.553321123123169,
+      "learning_rate": 0.001,
+      "loss": 3.8086,
+      "step": 4
+    },
+    {
+      "epoch": 0.041666666666666664,
+      "grad_norm": 2.8816118240356445,
+      "learning_rate": 0.001,
+      "loss": 3.4878,
+      "step": 5
+    },
+    {
+      "epoch": 0.041666666666666664,
+      "eval_runtime": 3.5452,
+      "eval_samples_per_second": 33.849,
+      "eval_steps_per_second": 8.462,
+      "step": 5
+    },
+    {
+      "epoch": 0.05,
+      "grad_norm": NaN,
+      "learning_rate": 0.001,
+      "loss": 3.0569,
+      "step": 6
+    },
+    {
+      "epoch": 0.058333333333333334,
+      "grad_norm": 2.565500020980835,
+      "learning_rate": 0.001,
+      "loss": 2.9872,
+      "step": 7
+    },
+    {
+      "epoch": 0.06666666666666667,
+      "grad_norm": 2.421236753463745,
+      "learning_rate": 0.001,
+      "loss": 2.2461,
+      "step": 8
+    },
+    {
+      "epoch": 0.075,
+      "grad_norm": 2.8918418884277344,
+      "learning_rate": 0.001,
+      "loss": 1.7755,
+      "step": 9
+    },
+    {
+      "epoch": 0.08333333333333333,
+      "grad_norm": 3.7322306632995605,
+      "learning_rate": 0.001,
+      "loss": 1.4434,
+      "step": 10
+    },
+    {
+      "epoch": 0.08333333333333333,
+      "eval_runtime": 3.5538,
+      "eval_samples_per_second": 33.766,
+      "eval_steps_per_second": 8.442,
+      "step": 10
+    },
+    {
+      "epoch": 0.09166666666666666,
+      "grad_norm": 3.7344257831573486,
+      "learning_rate": 0.001,
+      "loss": 1.3937,
+      "step": 11
+    },
+    {
+      "epoch": 0.1,
+      "grad_norm": 5.106380939483643,
+      "learning_rate": 0.001,
+      "loss": 1.3341,
+      "step": 12
+    },
+    {
+      "epoch": 0.10833333333333334,
+      "grad_norm": 2.572021245956421,
+      "learning_rate": 0.001,
+      "loss": 0.9658,
+      "step": 13
+    },
+    {
+      "epoch": 0.11666666666666667,
+      "grad_norm": 4.370708465576172,
+      "learning_rate": 0.001,
+      "loss": 1.1247,
+      "step": 14
+    },
+    {
+      "epoch": 0.125,
+      "grad_norm": 2.2091898918151855,
+      "learning_rate": 0.001,
+      "loss": 0.8327,
+      "step": 15
+    },
+    {
+      "epoch": 0.125,
+      "eval_runtime": 3.5597,
+      "eval_samples_per_second": 33.711,
+      "eval_steps_per_second": 8.428,
+      "step": 15
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 5.971612930297852,
+      "learning_rate": 0.001,
+      "loss": 0.7193,
+      "step": 16
+    },
+    {
+      "epoch": 0.14166666666666666,
+      "grad_norm": 2.8852627277374268,
+      "learning_rate": 0.001,
+      "loss": 0.6945,
+      "step": 17
+    },
+    {
+      "epoch": 0.15,
+      "grad_norm": 2.9274704456329346,
+      "learning_rate": 0.001,
+      "loss": 0.7308,
+      "step": 18
+    },
+    {
+      "epoch": 0.15833333333333333,
+      "grad_norm": 1.9048141241073608,
+      "learning_rate": 0.001,
+      "loss": 0.6461,
+      "step": 19
+    },
+    {
+      "epoch": 0.16666666666666666,
+      "grad_norm": 1.8781129121780396,
+      "learning_rate": 0.001,
+      "loss": 0.6144,
+      "step": 20
+    },
+    {
+      "epoch": 0.16666666666666666,
+      "eval_runtime": 3.5692,
+      "eval_samples_per_second": 33.621,
+      "eval_steps_per_second": 8.405,
+      "step": 20
+    },
+    {
+      "epoch": 0.175,
+      "grad_norm": 2.35707950592041,
+      "learning_rate": 0.001,
+      "loss": 0.8558,
+      "step": 21
+    },
+    {
+      "epoch": 0.18333333333333332,
+      "grad_norm": 2.049520254135132,
+      "learning_rate": 0.001,
+      "loss": 0.6385,
+      "step": 22
+    },
+    {
+      "epoch": 0.19166666666666668,
+      "grad_norm": 2.3720197677612305,
+      "learning_rate": 0.001,
+      "loss": 0.9522,
+      "step": 23
+    },
+    {
+      "epoch": 0.2,
+      "grad_norm": 1.980618953704834,
+      "learning_rate": 0.001,
+      "loss": 0.8766,
+      "step": 24
+    },
+    {
+      "epoch": 0.20833333333333334,
+      "grad_norm": 1.5879499912261963,
+      "learning_rate": 0.001,
+      "loss": 0.729,
+      "step": 25
+    },
+    {
+      "epoch": 0.20833333333333334,
+      "eval_runtime": 3.5755,
+      "eval_samples_per_second": 33.562,
+      "eval_steps_per_second": 8.391,
+      "step": 25
+    },
+    {
+      "epoch": 0.21666666666666667,
+      "grad_norm": 1.6505706310272217,
+      "learning_rate": 0.001,
+      "loss": 0.6637,
+      "step": 26
+    },
+    {
+      "epoch": 0.225,
+      "grad_norm": 1.4267758131027222,
+      "learning_rate": 0.001,
+      "loss": 0.9298,
+      "step": 27
+    },
+    {
+      "epoch": 0.23333333333333334,
+      "grad_norm": 1.1863181591033936,
+      "learning_rate": 0.001,
+      "loss": 0.5314,
+      "step": 28
+    },
+    {
+      "epoch": 0.24166666666666667,
+      "grad_norm": 1.2047488689422607,
+      "learning_rate": 0.001,
+      "loss": 0.4791,
+      "step": 29
+    },
+    {
+      "epoch": 0.25,
+      "grad_norm": 1.4940290451049805,
+      "learning_rate": 0.001,
+      "loss": 0.6757,
+      "step": 30
+    },
+    {
+      "epoch": 0.25,
+      "eval_runtime": 3.5813,
+      "eval_samples_per_second": 33.507,
+      "eval_steps_per_second": 8.377,
+      "step": 30
+    },
+    {
+      "epoch": 0.25833333333333336,
+      "grad_norm": 1.8670457601547241,
+      "learning_rate": 0.001,
+      "loss": 0.9796,
+      "step": 31
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 1.746319055557251,
+      "learning_rate": 0.001,
+      "loss": 0.73,
+      "step": 32
+    },
+    {
+      "epoch": 0.275,
+      "grad_norm": 1.3656867742538452,
+      "learning_rate": 0.001,
+      "loss": 0.6216,
+      "step": 33
+    },
+    {
+      "epoch": 0.2833333333333333,
+      "grad_norm": 1.6293808221817017,
+      "learning_rate": 0.001,
+      "loss": 0.7004,
+      "step": 34
+    },
+    {
+      "epoch": 0.2916666666666667,
+      "grad_norm": 1.2870112657546997,
+      "learning_rate": 0.001,
+      "loss": 0.5613,
+      "step": 35
+    },
+    {
+      "epoch": 0.2916666666666667,
+      "eval_runtime": 3.588,
+      "eval_samples_per_second": 33.445,
+      "eval_steps_per_second": 8.361,
+      "step": 35
+    },
+    {
+      "epoch": 0.3,
+      "grad_norm": 1.688391089439392,
+      "learning_rate": 0.001,
+      "loss": 1.0115,
+      "step": 36
+    },
+    {
+      "epoch": 0.30833333333333335,
+      "grad_norm": 1.2139495611190796,
+      "learning_rate": 0.001,
+      "loss": 0.5916,
+      "step": 37
+    },
+    {
+      "epoch": 0.31666666666666665,
+      "grad_norm": 1.4497591257095337,
+      "learning_rate": 0.001,
+      "loss": 0.6898,
+      "step": 38
+    },
+    {
+      "epoch": 0.325,
+      "grad_norm": 1.30401611328125,
+      "learning_rate": 0.001,
+      "loss": 0.52,
+      "step": 39
+    },
+    {
+      "epoch": 0.3333333333333333,
+      "grad_norm": 1.073735237121582,
+      "learning_rate": 0.001,
+      "loss": 0.6473,
+      "step": 40
+    },
+    {
+      "epoch": 0.3333333333333333,
+      "eval_runtime": 3.5897,
+      "eval_samples_per_second": 33.429,
+      "eval_steps_per_second": 8.357,
+      "step": 40
+    },
+    {
+      "epoch": 0.3416666666666667,
+      "grad_norm": 1.5980756282806396,
+      "learning_rate": 0.001,
+      "loss": 0.8344,
+      "step": 41
+    },
+    {
+      "epoch": 0.35,
+      "grad_norm": 1.258363127708435,
+      "learning_rate": 0.001,
+      "loss": 0.6081,
+      "step": 42
+    },
+    {
+      "epoch": 0.35833333333333334,
+      "grad_norm": 1.024636149406433,
+      "learning_rate": 0.001,
+      "loss": 0.6289,
+      "step": 43
+    },
+    {
+      "epoch": 0.36666666666666664,
+      "grad_norm": 1.5615390539169312,
+      "learning_rate": 0.001,
+      "loss": 0.7437,
+      "step": 44
+    },
+    {
+      "epoch": 0.375,
+      "grad_norm": 0.8973283767700195,
+      "learning_rate": 0.001,
+      "loss": 0.4438,
+      "step": 45
+    },
+    {
+      "epoch": 0.375,
+      "eval_runtime": 3.5911,
+      "eval_samples_per_second": 33.416,
+      "eval_steps_per_second": 8.354,
+      "step": 45
+    },
+    {
+      "epoch": 0.38333333333333336,
+      "grad_norm": 1.1488583087921143,
+      "learning_rate": 0.001,
+      "loss": 0.5021,
+      "step": 46
+    },
+    {
+      "epoch": 0.39166666666666666,
+      "grad_norm": 1.375650405883789,
+      "learning_rate": 0.001,
+      "loss": 0.6016,
+      "step": 47
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 1.5815932750701904,
+      "learning_rate": 0.001,
+      "loss": 0.6879,
+      "step": 48
+    },
+    {
+      "epoch": 0.4083333333333333,
+      "grad_norm": 1.1033896207809448,
+      "learning_rate": 0.001,
+      "loss": 0.3819,
+      "step": 49
+    },
+    {
+      "epoch": 0.4166666666666667,
+      "grad_norm": 1.599068522453308,
+      "learning_rate": 0.001,
+      "loss": 0.8746,
+      "step": 50
+    },
+    {
+      "epoch": 0.4166666666666667,
+      "eval_runtime": 3.595,
+      "eval_samples_per_second": 33.38,
+      "eval_steps_per_second": 8.345,
+      "step": 50
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 1200,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 10,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 555193368576000.0,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}