Upload folder using huggingface_hub

README.md

@@ -1,3 +1,220 @@
 ---
-license: apache-2.0
+library_name: peft
+base_model: mistralai/Mistral-7B-v0.1
 ---
+
+# 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]
+
+
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: False
+- load_in_4bit: True
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: True
+- bnb_4bit_compute_dtype: bfloat16
+
+### Framework versions
+
+
+- PEFT 0.6.3.dev0

adapter_config.json

@@ -0,0 +1,29 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "v_proj",
+    "lm_head",
+    "gate_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4c9908eaf5b57e25f51feb62dce86a0ca6495fd6cffe0db54f46a8d0e35c2ee
+size 85100592

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49b0f3b68162daa429f96d6924f555c99d0a088ac6eff7504061c06826bdc554
+size 43127132

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ffed6d4f513eefea1bbd2e6d94b0c2ee7dba23cd38e7ff8e5de5c5fa5fdae612
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eedfec4bc6f5a00a07b48568793720af057cf404e35f584cd69e8f806039a34d
+size 1064

trainer_state.json

@@ -0,0 +1,300 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.8560727661851257,
+  "eval_steps": 20,
+  "global_step": 400,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04,
+      "learning_rate": 1.9325842696629215e-05,
+      "loss": 1.8283,
+      "step": 20
+    },
+    {
+      "epoch": 0.04,
+      "eval_loss": 1.7597882747650146,
+      "eval_runtime": 167.9254,
+      "eval_samples_per_second": 2.65,
+      "eval_steps_per_second": 0.268,
+      "step": 20
+    },
+    {
+      "epoch": 0.09,
+      "learning_rate": 1.8426966292134835e-05,
+      "loss": 1.7181,
+      "step": 40
+    },
+    {
+      "epoch": 0.09,
+      "eval_loss": 1.7029485702514648,
+      "eval_runtime": 168.0408,
+      "eval_samples_per_second": 2.648,
+      "eval_steps_per_second": 0.268,
+      "step": 40
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 1.752808988764045e-05,
+      "loss": 1.6777,
+      "step": 60
+    },
+    {
+      "epoch": 0.13,
+      "eval_loss": 1.6699800491333008,
+      "eval_runtime": 167.9993,
+      "eval_samples_per_second": 2.649,
+      "eval_steps_per_second": 0.268,
+      "step": 60
+    },
+    {
+      "epoch": 0.17,
+      "learning_rate": 1.662921348314607e-05,
+      "loss": 1.6555,
+      "step": 80
+    },
+    {
+      "epoch": 0.17,
+      "eval_loss": 1.6510975360870361,
+      "eval_runtime": 168.0236,
+      "eval_samples_per_second": 2.648,
+      "eval_steps_per_second": 0.268,
+      "step": 80
+    },
+    {
+      "epoch": 0.21,
+      "learning_rate": 1.5730337078651687e-05,
+      "loss": 1.6371,
+      "step": 100
+    },
+    {
+      "epoch": 0.21,
+      "eval_loss": 1.6391140222549438,
+      "eval_runtime": 167.9874,
+      "eval_samples_per_second": 2.649,
+      "eval_steps_per_second": 0.268,
+      "step": 100
+    },
+    {
+      "epoch": 0.26,
+      "learning_rate": 1.4831460674157305e-05,
+      "loss": 1.638,
+      "step": 120
+    },
+    {
+      "epoch": 0.26,
+      "eval_loss": 1.6307817697525024,
+      "eval_runtime": 167.9676,
+      "eval_samples_per_second": 2.649,
+      "eval_steps_per_second": 0.268,
+      "step": 120
+    },
+    {
+      "epoch": 0.3,
+      "learning_rate": 1.3932584269662923e-05,
+      "loss": 1.6334,
+      "step": 140
+    },
+    {
+      "epoch": 0.3,
+      "eval_loss": 1.6237455606460571,
+      "eval_runtime": 167.9795,
+      "eval_samples_per_second": 2.649,
+      "eval_steps_per_second": 0.268,
+      "step": 140
+    },
+    {
+      "epoch": 0.34,
+      "learning_rate": 1.303370786516854e-05,
+      "loss": 1.6568,
+      "step": 160
+    },
+    {
+      "epoch": 0.34,
+      "eval_loss": 1.6185747385025024,
+      "eval_runtime": 167.9491,
+      "eval_samples_per_second": 2.65,
+      "eval_steps_per_second": 0.268,
+      "step": 160
+    },
+    {
+      "epoch": 0.39,
+      "learning_rate": 1.213483146067416e-05,
+      "loss": 1.6095,
+      "step": 180
+    },
+    {
+      "epoch": 0.39,
+      "eval_loss": 1.6145987510681152,
+      "eval_runtime": 167.8883,
+      "eval_samples_per_second": 2.651,
+      "eval_steps_per_second": 0.268,
+      "step": 180
+    },
+    {
+      "epoch": 0.43,
+      "learning_rate": 1.1235955056179778e-05,
+      "loss": 1.6347,
+      "step": 200
+    },
+    {
+      "epoch": 0.43,
+      "eval_loss": 1.6116222143173218,
+      "eval_runtime": 167.9012,
+      "eval_samples_per_second": 2.65,
+      "eval_steps_per_second": 0.268,
+      "step": 200
+    },
+    {
+      "epoch": 0.47,
+      "learning_rate": 1.0337078651685396e-05,
+      "loss": 1.6201,
+      "step": 220
+    },
+    {
+      "epoch": 0.47,
+      "eval_loss": 1.608642339706421,
+      "eval_runtime": 168.0086,
+      "eval_samples_per_second": 2.649,
+      "eval_steps_per_second": 0.268,
+      "step": 220
+    },
+    {
+      "epoch": 0.51,
+      "learning_rate": 9.438202247191012e-06,
+      "loss": 1.5781,
+      "step": 240
+    },
+    {
+      "epoch": 0.51,
+      "eval_loss": 1.6063767671585083,
+      "eval_runtime": 167.9056,
+      "eval_samples_per_second": 2.65,
+      "eval_steps_per_second": 0.268,
+      "step": 240
+    },
+    {
+      "epoch": 0.56,
+      "learning_rate": 8.53932584269663e-06,
+      "loss": 1.6158,
+      "step": 260
+    },
+    {
+      "epoch": 0.56,
+      "eval_loss": 1.6039100885391235,
+      "eval_runtime": 286.9359,
+      "eval_samples_per_second": 1.551,
+      "eval_steps_per_second": 0.157,
+      "step": 260
+    },
+    {
+      "epoch": 0.6,
+      "learning_rate": 7.640449438202247e-06,
+      "loss": 1.6098,
+      "step": 280
+    },
+    {
+      "epoch": 0.6,
+      "eval_loss": 1.602189540863037,
+      "eval_runtime": 336.0332,
+      "eval_samples_per_second": 1.324,
+      "eval_steps_per_second": 0.134,
+      "step": 280
+    },
+    {
+      "epoch": 0.64,
+      "learning_rate": 6.741573033707865e-06,
+      "loss": 1.6083,
+      "step": 300
+    },
+    {
+      "epoch": 0.64,
+      "eval_loss": 1.6008193492889404,
+      "eval_runtime": 333.4484,
+      "eval_samples_per_second": 1.335,
+      "eval_steps_per_second": 0.135,
+      "step": 300
+    },
+    {
+      "epoch": 0.68,
+      "learning_rate": 5.842696629213483e-06,
+      "loss": 1.596,
+      "step": 320
+    },
+    {
+      "epoch": 0.68,
+      "eval_loss": 1.5991967916488647,
+      "eval_runtime": 333.495,
+      "eval_samples_per_second": 1.334,
+      "eval_steps_per_second": 0.135,
+      "step": 320
+    },
+    {
+      "epoch": 0.73,
+      "learning_rate": 4.943820224719101e-06,
+      "loss": 1.6007,
+      "step": 340
+    },
+    {
+      "epoch": 0.73,
+      "eval_loss": 1.598080039024353,
+      "eval_runtime": 333.0437,
+      "eval_samples_per_second": 1.336,
+      "eval_steps_per_second": 0.135,
+      "step": 340
+    },
+    {
+      "epoch": 0.77,
+      "learning_rate": 4.04494382022472e-06,
+      "loss": 1.6234,
+      "step": 360
+    },
+    {
+      "epoch": 0.77,
+      "eval_loss": 1.5969579219818115,
+      "eval_runtime": 336.627,
+      "eval_samples_per_second": 1.322,
+      "eval_steps_per_second": 0.134,
+      "step": 360
+    },
+    {
+      "epoch": 0.81,
+      "learning_rate": 3.146067415730337e-06,
+      "loss": 1.6078,
+      "step": 380
+    },
+    {
+      "epoch": 0.81,
+      "eval_loss": 1.5960769653320312,
+      "eval_runtime": 333.84,
+      "eval_samples_per_second": 1.333,
+      "eval_steps_per_second": 0.135,
+      "step": 380
+    },
+    {
+      "epoch": 0.86,
+      "learning_rate": 2.2471910112359554e-06,
+      "loss": 1.5983,
+      "step": 400
+    },
+    {
+      "epoch": 0.86,
+      "eval_loss": 1.5955034494400024,
+      "eval_runtime": 335.6186,
+      "eval_samples_per_second": 1.326,
+      "eval_steps_per_second": 0.134,
+      "step": 400
+    }
+  ],
+  "logging_steps": 20,
+  "max_steps": 450,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 20,
+  "total_flos": 2.804385205714944e+17,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:75dba7c5f891acdcd82aeb8bc8677541948c16cf3e42df5cb5a12220cc740514
+size 4664