Upload 8 files

README.md

@@ -0,0 +1,204 @@
+---
+library_name: peft
+base_model: upstage/SOLAR-10.7B-Instruct-v1.0
+---
+
+# 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 0.7.2.dev0

adapter_config.json

@@ -0,0 +1,33 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "upstage/SOLAR-10.7B-Instruct-v1.0",
+  "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": 64,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "k_proj",
+    "lm_head",
+    "o_proj",
+    "gate_proj",
+    "down_proj",
+    "v_proj",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8616384d00ec936379a521191cecd37a3cf3ef1146622102beb1afb3439cb593
+size 1032316248

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a256d55644994b45a48ea6dffea8c34071d34209ae218b20ca7ac95e96c4bbf
+size 255268380

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af38663b1ea62fea1b780476d9b5891995a405dbbf64c0134ef2b8dd38aebab2
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc4ab5f608c113ef9b81b5921bd661a21962184c52075538ed871611015781ce
+size 1064

trainer_state.json

@@ -0,0 +1,301 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 3.1847133757961785,
+  "eval_steps": 25,
+  "global_step": 500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.16,
+      "learning_rate": 2.3797595190380762e-05,
+      "loss": 1.5869,
+      "step": 25
+    },
+    {
+      "epoch": 0.16,
+      "eval_loss": 1.343457579612732,
+      "eval_runtime": 45.0202,
+      "eval_samples_per_second": 6.775,
+      "eval_steps_per_second": 0.444,
+      "step": 25
+    },
+    {
+      "epoch": 0.32,
+      "learning_rate": 2.2545090180360722e-05,
+      "loss": 0.998,
+      "step": 50
+    },
+    {
+      "epoch": 0.32,
+      "eval_loss": 1.230006456375122,
+      "eval_runtime": 45.0029,
+      "eval_samples_per_second": 6.777,
+      "eval_steps_per_second": 0.444,
+      "step": 50
+    },
+    {
+      "epoch": 0.48,
+      "learning_rate": 2.1292585170340683e-05,
+      "loss": 0.8627,
+      "step": 75
+    },
+    {
+      "epoch": 0.48,
+      "eval_loss": 1.1211909055709839,
+      "eval_runtime": 45.0426,
+      "eval_samples_per_second": 6.771,
+      "eval_steps_per_second": 0.444,
+      "step": 75
+    },
+    {
+      "epoch": 0.64,
+      "learning_rate": 2.0040080160320643e-05,
+      "loss": 0.8958,
+      "step": 100
+    },
+    {
+      "epoch": 0.64,
+      "eval_loss": 1.1045145988464355,
+      "eval_runtime": 45.2025,
+      "eval_samples_per_second": 6.747,
+      "eval_steps_per_second": 0.442,
+      "step": 100
+    },
+    {
+      "epoch": 0.8,
+      "learning_rate": 1.87875751503006e-05,
+      "loss": 0.8205,
+      "step": 125
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 1.0842006206512451,
+      "eval_runtime": 45.2525,
+      "eval_samples_per_second": 6.74,
+      "eval_steps_per_second": 0.442,
+      "step": 125
+    },
+    {
+      "epoch": 0.96,
+      "learning_rate": 1.7535070140280564e-05,
+      "loss": 0.8141,
+      "step": 150
+    },
+    {
+      "epoch": 0.96,
+      "eval_loss": 1.0894731283187866,
+      "eval_runtime": 45.1805,
+      "eval_samples_per_second": 6.751,
+      "eval_steps_per_second": 0.443,
+      "step": 150
+    },
+    {
+      "epoch": 1.11,
+      "learning_rate": 1.628256513026052e-05,
+      "loss": 0.6384,
+      "step": 175
+    },
+    {
+      "epoch": 1.11,
+      "eval_loss": 1.1109672784805298,
+      "eval_runtime": 45.2193,
+      "eval_samples_per_second": 6.745,
+      "eval_steps_per_second": 0.442,
+      "step": 175
+    },
+    {
+      "epoch": 1.27,
+      "learning_rate": 1.5030060120240483e-05,
+      "loss": 0.5813,
+      "step": 200
+    },
+    {
+      "epoch": 1.27,
+      "eval_loss": 1.1189604997634888,
+      "eval_runtime": 45.2591,
+      "eval_samples_per_second": 6.739,
+      "eval_steps_per_second": 0.442,
+      "step": 200
+    },
+    {
+      "epoch": 1.43,
+      "learning_rate": 1.3777555110220442e-05,
+      "loss": 0.568,
+      "step": 225
+    },
+    {
+      "epoch": 1.43,
+      "eval_loss": 1.1027684211730957,
+      "eval_runtime": 45.2328,
+      "eval_samples_per_second": 6.743,
+      "eval_steps_per_second": 0.442,
+      "step": 225
+    },
+    {
+      "epoch": 1.59,
+      "learning_rate": 1.25250501002004e-05,
+      "loss": 0.5605,
+      "step": 250
+    },
+    {
+      "epoch": 1.59,
+      "eval_loss": 1.1073968410491943,
+      "eval_runtime": 45.4023,
+      "eval_samples_per_second": 6.718,
+      "eval_steps_per_second": 0.441,
+      "step": 250
+    },
+    {
+      "epoch": 1.75,
+      "learning_rate": 1.1272545090180361e-05,
+      "loss": 0.6342,
+      "step": 275
+    },
+    {
+      "epoch": 1.75,
+      "eval_loss": 1.091808557510376,
+      "eval_runtime": 45.3362,
+      "eval_samples_per_second": 6.728,
+      "eval_steps_per_second": 0.441,
+      "step": 275
+    },
+    {
+      "epoch": 1.91,
+      "learning_rate": 1.0020040080160322e-05,
+      "loss": 0.5254,
+      "step": 300
+    },
+    {
+      "epoch": 1.91,
+      "eval_loss": 1.1066254377365112,
+      "eval_runtime": 45.2929,
+      "eval_samples_per_second": 6.734,
+      "eval_steps_per_second": 0.442,
+      "step": 300
+    },
+    {
+      "epoch": 2.07,
+      "learning_rate": 8.767535070140282e-06,
+      "loss": 0.4553,
+      "step": 325
+    },
+    {
+      "epoch": 2.07,
+      "eval_loss": 1.1803815364837646,
+      "eval_runtime": 45.0968,
+      "eval_samples_per_second": 6.763,
+      "eval_steps_per_second": 0.443,
+      "step": 325
+    },
+    {
+      "epoch": 2.23,
+      "learning_rate": 7.515030060120242e-06,
+      "loss": 0.3712,
+      "step": 350
+    },
+    {
+      "epoch": 2.23,
+      "eval_loss": 1.1674922704696655,
+      "eval_runtime": 45.0974,
+      "eval_samples_per_second": 6.763,
+      "eval_steps_per_second": 0.443,
+      "step": 350
+    },
+    {
+      "epoch": 2.39,
+      "learning_rate": 6.2625250501002e-06,
+      "loss": 0.363,
+      "step": 375
+    },
+    {
+      "epoch": 2.39,
+      "eval_loss": 1.180160403251648,
+      "eval_runtime": 45.1473,
+      "eval_samples_per_second": 6.756,
+      "eval_steps_per_second": 0.443,
+      "step": 375
+    },
+    {
+      "epoch": 2.55,
+      "learning_rate": 5.010020040080161e-06,
+      "loss": 0.3732,
+      "step": 400
+    },
+    {
+      "epoch": 2.55,
+      "eval_loss": 1.1637239456176758,
+      "eval_runtime": 45.18,
+      "eval_samples_per_second": 6.751,
+      "eval_steps_per_second": 0.443,
+      "step": 400
+    },
+    {
+      "epoch": 2.71,
+      "learning_rate": 3.757515030060121e-06,
+      "loss": 0.4188,
+      "step": 425
+    },
+    {
+      "epoch": 2.71,
+      "eval_loss": 1.1796648502349854,
+      "eval_runtime": 45.1853,
+      "eval_samples_per_second": 6.75,
+      "eval_steps_per_second": 0.443,
+      "step": 425
+    },
+    {
+      "epoch": 2.87,
+      "learning_rate": 2.5050100200400804e-06,
+      "loss": 0.3395,
+      "step": 450
+    },
+    {
+      "epoch": 2.87,
+      "eval_loss": 1.179069995880127,
+      "eval_runtime": 45.3296,
+      "eval_samples_per_second": 6.728,
+      "eval_steps_per_second": 0.441,
+      "step": 450
+    },
+    {
+      "epoch": 3.03,
+      "learning_rate": 1.2525050100200402e-06,
+      "loss": 0.3736,
+      "step": 475
+    },
+    {
+      "epoch": 3.03,
+      "eval_loss": 1.176107406616211,
+      "eval_runtime": 45.2686,
+      "eval_samples_per_second": 6.738,
+      "eval_steps_per_second": 0.442,
+      "step": 475
+    },
+    {
+      "epoch": 3.18,
+      "learning_rate": 0.0,
+      "loss": 0.2538,
+      "step": 500
+    },
+    {
+      "epoch": 3.18,
+      "eval_loss": 1.2055637836456299,
+      "eval_runtime": 45.3063,
+      "eval_samples_per_second": 6.732,
+      "eval_steps_per_second": 0.441,
+      "step": 500
+    }
+  ],
+  "logging_steps": 25,
+  "max_steps": 500,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 4,
+  "save_steps": 25,
+  "total_flos": 6.571164044781158e+16,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60200974bf9a7f61c8cba80a2cd4d2c208eccc1363eaf807b94972365fb6d498
+size 4664