Upload 6 files

README.md

@@ -0,0 +1,204 @@
+---
+library_name: peft
+base_model: microsoft/phi-2
+---
+
+# 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 0.8.2

adapter_config.json

@@ -0,0 +1,33 @@
+{
+  "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,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "fc1",
+    "o_proj",
+    "k_proj",
+    "fc2",
+    "q_proj",
+    "v_proj",
+    "dense",
+    "lm_head"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c291c66626fc4fc5b4412d264eea8e4cfa2742e7f6ce787e44b041cf96423e4
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7982f7dee31c1c2daf2099d171b25f3e55024f67d7a365b080d086328942b1d0
+size 1064

trainer_state.json

@@ -0,0 +1,201 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 6.0,
+  "eval_steps": 50,
+  "global_step": 450,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.33,
+      "learning_rate": 5.2354709418837674e-05,
+      "loss": 1.6331,
+      "step": 25
+    },
+    {
+      "epoch": 0.67,
+      "learning_rate": 4.959919839679359e-05,
+      "loss": 0.8124,
+      "step": 50
+    },
+    {
+      "epoch": 0.67,
+      "eval_loss": 2.1140503883361816,
+      "eval_runtime": 11.8386,
+      "eval_samples_per_second": 0.76,
+      "eval_steps_per_second": 0.169,
+      "step": 50
+    },
+    {
+      "epoch": 1.0,
+      "learning_rate": 4.68436873747495e-05,
+      "loss": 0.766,
+      "step": 75
+    },
+    {
+      "epoch": 1.33,
+      "learning_rate": 4.408817635270541e-05,
+      "loss": 0.562,
+      "step": 100
+    },
+    {
+      "epoch": 1.33,
+      "eval_loss": 1.9290642738342285,
+      "eval_runtime": 11.9715,
+      "eval_samples_per_second": 0.752,
+      "eval_steps_per_second": 0.167,
+      "step": 100
+    },
+    {
+      "epoch": 1.67,
+      "learning_rate": 4.133266533066132e-05,
+      "loss": 0.3301,
+      "step": 125
+    },
+    {
+      "epoch": 2.0,
+      "learning_rate": 3.8577154308617235e-05,
+      "loss": 0.3811,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.065908908843994,
+      "eval_runtime": 11.9277,
+      "eval_samples_per_second": 0.755,
+      "eval_steps_per_second": 0.168,
+      "step": 150
+    },
+    {
+      "epoch": 2.33,
+      "learning_rate": 3.582164328657315e-05,
+      "loss": 0.3086,
+      "step": 175
+    },
+    {
+      "epoch": 2.67,
+      "learning_rate": 3.306613226452906e-05,
+      "loss": 0.2969,
+      "step": 200
+    },
+    {
+      "epoch": 2.67,
+      "eval_loss": 2.2028963565826416,
+      "eval_runtime": 11.9591,
+      "eval_samples_per_second": 0.753,
+      "eval_steps_per_second": 0.167,
+      "step": 200
+    },
+    {
+      "epoch": 3.0,
+      "learning_rate": 3.0310621242484972e-05,
+      "loss": 0.2236,
+      "step": 225
+    },
+    {
+      "epoch": 3.33,
+      "learning_rate": 2.755511022044088e-05,
+      "loss": 0.2148,
+      "step": 250
+    },
+    {
+      "epoch": 3.33,
+      "eval_loss": 2.3397459983825684,
+      "eval_runtime": 11.8913,
+      "eval_samples_per_second": 0.757,
+      "eval_steps_per_second": 0.168,
+      "step": 250
+    },
+    {
+      "epoch": 3.67,
+      "learning_rate": 2.4799599198396796e-05,
+      "loss": 0.1813,
+      "step": 275
+    },
+    {
+      "epoch": 4.0,
+      "learning_rate": 2.2044088176352705e-05,
+      "loss": 0.2172,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.2869534492492676,
+      "eval_runtime": 11.8718,
+      "eval_samples_per_second": 0.758,
+      "eval_steps_per_second": 0.168,
+      "step": 300
+    },
+    {
+      "epoch": 4.33,
+      "learning_rate": 1.9288577154308618e-05,
+      "loss": 0.1436,
+      "step": 325
+    },
+    {
+      "epoch": 4.67,
+      "learning_rate": 1.653306613226453e-05,
+      "loss": 0.1659,
+      "step": 350
+    },
+    {
+      "epoch": 4.67,
+      "eval_loss": 2.3965632915496826,
+      "eval_runtime": 11.9151,
+      "eval_samples_per_second": 0.755,
+      "eval_steps_per_second": 0.168,
+      "step": 350
+    },
+    {
+      "epoch": 5.0,
+      "learning_rate": 1.377755511022044e-05,
+      "loss": 0.1664,
+      "step": 375
+    },
+    {
+      "epoch": 5.33,
+      "learning_rate": 1.1022044088176353e-05,
+      "loss": 0.1165,
+      "step": 400
+    },
+    {
+      "epoch": 5.33,
+      "eval_loss": 2.4968247413635254,
+      "eval_runtime": 11.858,
+      "eval_samples_per_second": 0.759,
+      "eval_steps_per_second": 0.169,
+      "step": 400
+    },
+    {
+      "epoch": 5.67,
+      "learning_rate": 8.266533066132265e-06,
+      "loss": 0.1572,
+      "step": 425
+    },
+    {
+      "epoch": 6.0,
+      "learning_rate": 5.511022044088176e-06,
+      "loss": 0.1174,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.4439687728881836,
+      "eval_runtime": 11.9003,
+      "eval_samples_per_second": 0.756,
+      "eval_steps_per_second": 0.168,
+      "step": 450
+    }
+  ],
+  "logging_steps": 25,
+  "max_steps": 500,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 7,
+  "save_steps": 50,
+  "total_flos": 1.104886503936e+16,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36a45f8f32ff02355d148bca24e55324966575569e9640f7ec93ad3c7c505334
+size 4856