Upload folder using huggingface_hub

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+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 0.13.1

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "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": 32,
+  "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": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96ad0134fcd4a8c4f39195ab79605c75fce9887a0ebf30de3f3886720bd536f7
+size 109069176

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+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 0.13.1

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "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": 32,
+  "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": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:055a21dc51404367f72f3cb3dfba97a6b704126a5389967feff27cbe4c99c92f
+size 109069176

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:33bd1beab6be2ede28487161dadb42d795a64f1d77fbe547ac8a5b4dd5ff5d3e
+size 55532538

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:758cc33c437deece43b1ec8a2ef658d4e76b2d038dbec6d577466f62ccd3a71e
+size 14244

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:35edfa8bea95e3d4902ce67741a255f6cf79b9ff66c7be346412ef380c2f3205
+size 1064

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "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": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/trainer_state.json

@@ -0,0 +1,143 @@
+{
+  "best_metric": 1.414519190788269,
+  "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-63",
+  "epoch": 5.0,
+  "eval_steps": 10,
+  "global_step": 105,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.47619047619047616,
+      "grad_norm": 1.5265194177627563,
+      "learning_rate": 0.0002,
+      "loss": 2.4633,
+      "step": 10
+    },
+    {
+      "epoch": 0.9523809523809523,
+      "grad_norm": 0.9496003985404968,
+      "learning_rate": 0.0002,
+      "loss": 2.1197,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 2.043581485748291,
+      "eval_runtime": 3.9252,
+      "eval_samples_per_second": 3.821,
+      "eval_steps_per_second": 0.51,
+      "step": 21
+    },
+    {
+      "epoch": 1.4285714285714286,
+      "grad_norm": 1.1841896772384644,
+      "learning_rate": 0.0002,
+      "loss": 1.7634,
+      "step": 30
+    },
+    {
+      "epoch": 1.9047619047619047,
+      "grad_norm": 0.9208888411521912,
+      "learning_rate": 0.0002,
+      "loss": 1.3481,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.4355663061141968,
+      "eval_runtime": 3.9703,
+      "eval_samples_per_second": 3.778,
+      "eval_steps_per_second": 0.504,
+      "step": 42
+    },
+    {
+      "epoch": 2.380952380952381,
+      "grad_norm": 0.9314467310905457,
+      "learning_rate": 0.0002,
+      "loss": 1.2091,
+      "step": 50
+    },
+    {
+      "epoch": 2.857142857142857,
+      "grad_norm": 0.8855467438697815,
+      "learning_rate": 0.0002,
+      "loss": 1.1729,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 1.414519190788269,
+      "eval_runtime": 2.5889,
+      "eval_samples_per_second": 5.794,
+      "eval_steps_per_second": 0.773,
+      "step": 63
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.1989318132400513,
+      "learning_rate": 0.0002,
+      "loss": 1.065,
+      "step": 70
+    },
+    {
+      "epoch": 3.8095238095238093,
+      "grad_norm": 1.4512395858764648,
+      "learning_rate": 0.0002,
+      "loss": 1.0268,
+      "step": 80
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.445521593093872,
+      "eval_runtime": 4.3744,
+      "eval_samples_per_second": 3.429,
+      "eval_steps_per_second": 0.457,
+      "step": 84
+    },
+    {
+      "epoch": 4.285714285714286,
+      "grad_norm": 1.9429545402526855,
+      "learning_rate": 0.0002,
+      "loss": 0.9177,
+      "step": 90
+    },
+    {
+      "epoch": 4.761904761904762,
+      "grad_norm": 1.614206314086914,
+      "learning_rate": 0.0002,
+      "loss": 0.8502,
+      "step": 100
+    },
+    {
+      "epoch": 5.0,
+      "eval_loss": 1.5487611293792725,
+      "eval_runtime": 4.0863,
+      "eval_samples_per_second": 3.671,
+      "eval_steps_per_second": 0.489,
+      "step": 105
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 168,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 8,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 4606846304256000.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-105/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d72a6c83683f93f58baa7655aae441b2de09a241d61284bf4d42e8a028cd670d
+size 5560

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+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 0.13.1

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "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": 32,
+  "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": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8496d69d57b99555858a9642427017bc44721956496dacfeb370987fdb376cd1
+size 109069176

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eddaa52365c05c3d01ef0fcd60085a990328ba31cb03d1cde898df735f21b505
+size 55532538

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f2f19524e8c3f13c6f9d818986578060e3712d854258fbe327f7e54a8c1d7fb
+size 14244

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3d829a2c582255f48447ae34872c1e125d881beba555f88fc957c4c789c4b7e5
+size 1064

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "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": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/trainer_state.json

@@ -0,0 +1,165 @@
+{
+  "best_metric": 1.414519190788269,
+  "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-63",
+  "epoch": 6.0,
+  "eval_steps": 10,
+  "global_step": 126,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.47619047619047616,
+      "grad_norm": 1.5265194177627563,
+      "learning_rate": 0.0002,
+      "loss": 2.4633,
+      "step": 10
+    },
+    {
+      "epoch": 0.9523809523809523,
+      "grad_norm": 0.9496003985404968,
+      "learning_rate": 0.0002,
+      "loss": 2.1197,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 2.043581485748291,
+      "eval_runtime": 3.9252,
+      "eval_samples_per_second": 3.821,
+      "eval_steps_per_second": 0.51,
+      "step": 21
+    },
+    {
+      "epoch": 1.4285714285714286,
+      "grad_norm": 1.1841896772384644,
+      "learning_rate": 0.0002,
+      "loss": 1.7634,
+      "step": 30
+    },
+    {
+      "epoch": 1.9047619047619047,
+      "grad_norm": 0.9208888411521912,
+      "learning_rate": 0.0002,
+      "loss": 1.3481,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.4355663061141968,
+      "eval_runtime": 3.9703,
+      "eval_samples_per_second": 3.778,
+      "eval_steps_per_second": 0.504,
+      "step": 42
+    },
+    {
+      "epoch": 2.380952380952381,
+      "grad_norm": 0.9314467310905457,
+      "learning_rate": 0.0002,
+      "loss": 1.2091,
+      "step": 50
+    },
+    {
+      "epoch": 2.857142857142857,
+      "grad_norm": 0.8855467438697815,
+      "learning_rate": 0.0002,
+      "loss": 1.1729,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 1.414519190788269,
+      "eval_runtime": 2.5889,
+      "eval_samples_per_second": 5.794,
+      "eval_steps_per_second": 0.773,
+      "step": 63
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.1989318132400513,
+      "learning_rate": 0.0002,
+      "loss": 1.065,
+      "step": 70
+    },
+    {
+      "epoch": 3.8095238095238093,
+      "grad_norm": 1.4512395858764648,
+      "learning_rate": 0.0002,
+      "loss": 1.0268,
+      "step": 80
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.445521593093872,
+      "eval_runtime": 4.3744,
+      "eval_samples_per_second": 3.429,
+      "eval_steps_per_second": 0.457,
+      "step": 84
+    },
+    {
+      "epoch": 4.285714285714286,
+      "grad_norm": 1.9429545402526855,
+      "learning_rate": 0.0002,
+      "loss": 0.9177,
+      "step": 90
+    },
+    {
+      "epoch": 4.761904761904762,
+      "grad_norm": 1.614206314086914,
+      "learning_rate": 0.0002,
+      "loss": 0.8502,
+      "step": 100
+    },
+    {
+      "epoch": 5.0,
+      "eval_loss": 1.5487611293792725,
+      "eval_runtime": 4.0863,
+      "eval_samples_per_second": 3.671,
+      "eval_steps_per_second": 0.489,
+      "step": 105
+    },
+    {
+      "epoch": 5.238095238095238,
+      "grad_norm": 1.669851303100586,
+      "learning_rate": 0.0002,
+      "loss": 0.7918,
+      "step": 110
+    },
+    {
+      "epoch": 5.714285714285714,
+      "grad_norm": 1.8277592658996582,
+      "learning_rate": 0.0002,
+      "loss": 0.7221,
+      "step": 120
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.6458890438079834,
+      "eval_runtime": 2.7471,
+      "eval_samples_per_second": 5.46,
+      "eval_steps_per_second": 0.728,
+      "step": 126
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 168,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 8,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5528215565107200.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-126/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d72a6c83683f93f58baa7655aae441b2de09a241d61284bf4d42e8a028cd670d
+size 5560

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+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 0.13.1

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "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": 32,
+  "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": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b8506101265cd91c8c697c6c4dadaa603bad5f6ed87f0fd95d8b8b95e32a29e
+size 109069176

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87ea21a7b4050ecc779e150b3dd6d8b28023321ca2b041a63ad63f402d99fed2
+size 55532538

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1a8f3304359abfad868a1cede3057024408b0a84bb03a33e12e99f7b1bc8a1d1
+size 14244

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71a9f5272dca00a67a663299f7fc10187d6643ce612719de5c600d2a9add79bf
+size 1064

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "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": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/trainer_state.json

@@ -0,0 +1,187 @@
+{
+  "best_metric": 1.414519190788269,
+  "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-63",
+  "epoch": 7.0,
+  "eval_steps": 10,
+  "global_step": 147,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.47619047619047616,
+      "grad_norm": 1.5265194177627563,
+      "learning_rate": 0.0002,
+      "loss": 2.4633,
+      "step": 10
+    },
+    {
+      "epoch": 0.9523809523809523,
+      "grad_norm": 0.9496003985404968,
+      "learning_rate": 0.0002,
+      "loss": 2.1197,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 2.043581485748291,
+      "eval_runtime": 3.9252,
+      "eval_samples_per_second": 3.821,
+      "eval_steps_per_second": 0.51,
+      "step": 21
+    },
+    {
+      "epoch": 1.4285714285714286,
+      "grad_norm": 1.1841896772384644,
+      "learning_rate": 0.0002,
+      "loss": 1.7634,
+      "step": 30
+    },
+    {
+      "epoch": 1.9047619047619047,
+      "grad_norm": 0.9208888411521912,
+      "learning_rate": 0.0002,
+      "loss": 1.3481,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.4355663061141968,
+      "eval_runtime": 3.9703,
+      "eval_samples_per_second": 3.778,
+      "eval_steps_per_second": 0.504,
+      "step": 42
+    },
+    {
+      "epoch": 2.380952380952381,
+      "grad_norm": 0.9314467310905457,
+      "learning_rate": 0.0002,
+      "loss": 1.2091,
+      "step": 50
+    },
+    {
+      "epoch": 2.857142857142857,
+      "grad_norm": 0.8855467438697815,
+      "learning_rate": 0.0002,
+      "loss": 1.1729,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 1.414519190788269,
+      "eval_runtime": 2.5889,
+      "eval_samples_per_second": 5.794,
+      "eval_steps_per_second": 0.773,
+      "step": 63
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.1989318132400513,
+      "learning_rate": 0.0002,
+      "loss": 1.065,
+      "step": 70
+    },
+    {
+      "epoch": 3.8095238095238093,
+      "grad_norm": 1.4512395858764648,
+      "learning_rate": 0.0002,
+      "loss": 1.0268,
+      "step": 80
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.445521593093872,
+      "eval_runtime": 4.3744,
+      "eval_samples_per_second": 3.429,
+      "eval_steps_per_second": 0.457,
+      "step": 84
+    },
+    {
+      "epoch": 4.285714285714286,
+      "grad_norm": 1.9429545402526855,
+      "learning_rate": 0.0002,
+      "loss": 0.9177,
+      "step": 90
+    },
+    {
+      "epoch": 4.761904761904762,
+      "grad_norm": 1.614206314086914,
+      "learning_rate": 0.0002,
+      "loss": 0.8502,
+      "step": 100
+    },
+    {
+      "epoch": 5.0,
+      "eval_loss": 1.5487611293792725,
+      "eval_runtime": 4.0863,
+      "eval_samples_per_second": 3.671,
+      "eval_steps_per_second": 0.489,
+      "step": 105
+    },
+    {
+      "epoch": 5.238095238095238,
+      "grad_norm": 1.669851303100586,
+      "learning_rate": 0.0002,
+      "loss": 0.7918,
+      "step": 110
+    },
+    {
+      "epoch": 5.714285714285714,
+      "grad_norm": 1.8277592658996582,
+      "learning_rate": 0.0002,
+      "loss": 0.7221,
+      "step": 120
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.6458890438079834,
+      "eval_runtime": 2.7471,
+      "eval_samples_per_second": 5.46,
+      "eval_steps_per_second": 0.728,
+      "step": 126
+    },
+    {
+      "epoch": 6.190476190476191,
+      "grad_norm": 2.2401881217956543,
+      "learning_rate": 0.0002,
+      "loss": 0.6817,
+      "step": 130
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 1.618836760520935,
+      "learning_rate": 0.0002,
+      "loss": 0.6155,
+      "step": 140
+    },
+    {
+      "epoch": 7.0,
+      "eval_loss": 1.7682832479476929,
+      "eval_runtime": 3.9474,
+      "eval_samples_per_second": 3.8,
+      "eval_steps_per_second": 0.507,
+      "step": 147
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 168,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 8,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6449584825958400.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-147/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d72a6c83683f93f58baa7655aae441b2de09a241d61284bf4d42e8a028cd670d
+size 5560

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/README.md

@@ -0,0 +1,202 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+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 0.13.1

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "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": 32,
+  "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": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60193486e16baae78448113726bd27e45d4092af85e85dd6e68e13d942861123
+size 109069176

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38b6b81db54836fe81176110de1c0bf4240eded42e898c6aff0d1d87f6a6e610
+size 55532538

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:06a57fcbc6b414125db21b0af03ffd188e6a91404513e444752e1553227097da
+size 14244

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af2accd5ede0de683b26f58827147a120f856c0db448ae7e2b6ed6c56f66f5b8
+size 1064

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "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": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404

Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-168/trainer_state.json

@@ -0,0 +1,209 @@
+{
+  "best_metric": 1.414519190788269,
+  "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-0.4-num-354-sd-42/checkpoint-63",
+  "epoch": 8.0,
+  "eval_steps": 10,
+  "global_step": 168,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.47619047619047616,
+      "grad_norm": 1.5265194177627563,
+      "learning_rate": 0.0002,
+      "loss": 2.4633,
+      "step": 10
+    },
+    {
+      "epoch": 0.9523809523809523,
+      "grad_norm": 0.9496003985404968,
+      "learning_rate": 0.0002,
+      "loss": 2.1197,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 2.043581485748291,
+      "eval_runtime": 3.9252,
+      "eval_samples_per_second": 3.821,
+      "eval_steps_per_second": 0.51,
+      "step": 21
+    },
+    {
+      "epoch": 1.4285714285714286,
+      "grad_norm": 1.1841896772384644,
+      "learning_rate": 0.0002,
+      "loss": 1.7634,
+      "step": 30
+    },
+    {
+      "epoch": 1.9047619047619047,
+      "grad_norm": 0.9208888411521912,
+      "learning_rate": 0.0002,
+      "loss": 1.3481,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.4355663061141968,
+      "eval_runtime": 3.9703,
+      "eval_samples_per_second": 3.778,
+      "eval_steps_per_second": 0.504,
+      "step": 42
+    },
+    {
+      "epoch": 2.380952380952381,
+      "grad_norm": 0.9314467310905457,
+      "learning_rate": 0.0002,
+      "loss": 1.2091,
+      "step": 50
+    },
+    {
+      "epoch": 2.857142857142857,
+      "grad_norm": 0.8855467438697815,
+      "learning_rate": 0.0002,
+      "loss": 1.1729,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 1.414519190788269,
+      "eval_runtime": 2.5889,
+      "eval_samples_per_second": 5.794,
+      "eval_steps_per_second": 0.773,
+      "step": 63
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.1989318132400513,
+      "learning_rate": 0.0002,
+      "loss": 1.065,
+      "step": 70
+    },
+    {
+      "epoch": 3.8095238095238093,
+      "grad_norm": 1.4512395858764648,
+      "learning_rate": 0.0002,
+      "loss": 1.0268,
+      "step": 80
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 1.445521593093872,
+      "eval_runtime": 4.3744,
+      "eval_samples_per_second": 3.429,
+      "eval_steps_per_second": 0.457,
+      "step": 84
+    },
+    {
+      "epoch": 4.285714285714286,
+      "grad_norm": 1.9429545402526855,
+      "learning_rate": 0.0002,
+      "loss": 0.9177,
+      "step": 90
+    },
+    {
+      "epoch": 4.761904761904762,
+      "grad_norm": 1.614206314086914,
+      "learning_rate": 0.0002,
+      "loss": 0.8502,
+      "step": 100
+    },
+    {
+      "epoch": 5.0,
+      "eval_loss": 1.5487611293792725,
+      "eval_runtime": 4.0863,
+      "eval_samples_per_second": 3.671,
+      "eval_steps_per_second": 0.489,
+      "step": 105
+    },
+    {
+      "epoch": 5.238095238095238,
+      "grad_norm": 1.669851303100586,
+      "learning_rate": 0.0002,
+      "loss": 0.7918,
+      "step": 110
+    },
+    {
+      "epoch": 5.714285714285714,
+      "grad_norm": 1.8277592658996582,
+      "learning_rate": 0.0002,
+      "loss": 0.7221,
+      "step": 120
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 1.6458890438079834,
+      "eval_runtime": 2.7471,
+      "eval_samples_per_second": 5.46,
+      "eval_steps_per_second": 0.728,
+      "step": 126
+    },
+    {
+      "epoch": 6.190476190476191,
+      "grad_norm": 2.2401881217956543,
+      "learning_rate": 0.0002,
+      "loss": 0.6817,
+      "step": 130
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 1.618836760520935,
+      "learning_rate": 0.0002,
+      "loss": 0.6155,
+      "step": 140
+    },
+    {
+      "epoch": 7.0,
+      "eval_loss": 1.7682832479476929,
+      "eval_runtime": 3.9474,
+      "eval_samples_per_second": 3.8,
+      "eval_steps_per_second": 0.507,
+      "step": 147
+    },
+    {
+      "epoch": 7.142857142857143,
+      "grad_norm": 1.3816609382629395,
+      "learning_rate": 0.0002,
+      "loss": 0.5979,
+      "step": 150
+    },
+    {
+      "epoch": 7.619047619047619,
+      "grad_norm": 1.8603096008300781,
+      "learning_rate": 0.0002,
+      "loss": 0.5205,
+      "step": 160
+    },
+    {
+      "epoch": 8.0,
+      "eval_loss": 1.893521785736084,
+      "eval_runtime": 3.9748,
+      "eval_samples_per_second": 3.774,
+      "eval_steps_per_second": 0.503,
+      "step": 168
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 168,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 8,
+  "save_steps": 200,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7370954086809600.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}