test

README.md

@@ -0,0 +1,220 @@
+---
+library_name: peft
+base_model: microsoft/phi-1_5
+---
+
+# 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: True
+- load_in_4bit: False
+- 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: fp4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float32
+
+### Framework versions
+
+
+- PEFT 0.6.2

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e44ce263e6fd885f50d82ca515b9325375b43ee36ededb75acf161ce88bc2e41
+size 48

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07ecf16415dbb878d4224f58533a271f3d37bbb47bb8e2409e9eef0d3ced4390
+size 37829690

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7eb35b3d837d79632aedb5fff9f2929a3e6cbceeb2c50a27bf143f39407bf424
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee665d99b8d4ac37b6829a57abd01a01763b04846f27bc645d525d70173d6821
+size 1064

trainer_state.json

@@ -0,0 +1,419 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.18099547511312217,
+  "eval_steps": 20,
+  "global_step": 400,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.0,
+      "learning_rate": 2.9999999999999997e-05,
+      "loss": 2.4375,
+      "step": 10
+    },
+    {
+      "epoch": 0.01,
+      "learning_rate": 5.9999999999999995e-05,
+      "loss": 2.5231,
+      "step": 20
+    },
+    {
+      "epoch": 0.01,
+      "eval_loss": 2.4237778186798096,
+      "eval_runtime": 171.986,
+      "eval_samples_per_second": 45.69,
+      "eval_steps_per_second": 5.716,
+      "step": 20
+    },
+    {
+      "epoch": 0.01,
+      "learning_rate": 8.999999999999999e-05,
+      "loss": 2.3284,
+      "step": 30
+    },
+    {
+      "epoch": 0.02,
+      "learning_rate": 0.00011999999999999999,
+      "loss": 1.8222,
+      "step": 40
+    },
+    {
+      "epoch": 0.02,
+      "eval_loss": 1.525316596031189,
+      "eval_runtime": 172.7335,
+      "eval_samples_per_second": 45.492,
+      "eval_steps_per_second": 5.691,
+      "step": 40
+    },
+    {
+      "epoch": 0.02,
+      "learning_rate": 0.00015,
+      "loss": 1.025,
+      "step": 50
+    },
+    {
+      "epoch": 0.03,
+      "learning_rate": 0.00017999999999999998,
+      "loss": 1.0834,
+      "step": 60
+    },
+    {
+      "epoch": 0.03,
+      "eval_loss": 0.8071926832199097,
+      "eval_runtime": 172.0838,
+      "eval_samples_per_second": 45.664,
+      "eval_steps_per_second": 5.712,
+      "step": 60
+    },
+    {
+      "epoch": 0.03,
+      "learning_rate": 0.00020999999999999998,
+      "loss": 0.8541,
+      "step": 70
+    },
+    {
+      "epoch": 0.04,
+      "learning_rate": 0.00023999999999999998,
+      "loss": 0.7104,
+      "step": 80
+    },
+    {
+      "epoch": 0.04,
+      "eval_loss": 0.7147021889686584,
+      "eval_runtime": 172.8542,
+      "eval_samples_per_second": 45.46,
+      "eval_steps_per_second": 5.687,
+      "step": 80
+    },
+    {
+      "epoch": 0.04,
+      "learning_rate": 0.00027,
+      "loss": 0.6001,
+      "step": 90
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 0.0003,
+      "loss": 0.4885,
+      "step": 100
+    },
+    {
+      "epoch": 0.05,
+      "eval_loss": 0.70524662733078,
+      "eval_runtime": 172.2659,
+      "eval_samples_per_second": 45.616,
+      "eval_steps_per_second": 5.706,
+      "step": 100
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 0.00029,
+      "loss": 0.9048,
+      "step": 110
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 0.00028,
+      "loss": 0.7366,
+      "step": 120
+    },
+    {
+      "epoch": 0.05,
+      "eval_loss": 0.6695398688316345,
+      "eval_runtime": 172.5803,
+      "eval_samples_per_second": 45.532,
+      "eval_steps_per_second": 5.696,
+      "step": 120
+    },
+    {
+      "epoch": 0.06,
+      "learning_rate": 0.00027,
+      "loss": 0.6551,
+      "step": 130
+    },
+    {
+      "epoch": 0.06,
+      "learning_rate": 0.00026,
+      "loss": 0.5573,
+      "step": 140
+    },
+    {
+      "epoch": 0.06,
+      "eval_loss": 0.6578989624977112,
+      "eval_runtime": 172.8835,
+      "eval_samples_per_second": 45.453,
+      "eval_steps_per_second": 5.686,
+      "step": 140
+    },
+    {
+      "epoch": 0.07,
+      "learning_rate": 0.00025,
+      "loss": 0.4508,
+      "step": 150
+    },
+    {
+      "epoch": 0.07,
+      "learning_rate": 0.00023999999999999998,
+      "loss": 0.8456,
+      "step": 160
+    },
+    {
+      "epoch": 0.07,
+      "eval_loss": 0.6626420021057129,
+      "eval_runtime": 172.8197,
+      "eval_samples_per_second": 45.469,
+      "eval_steps_per_second": 5.688,
+      "step": 160
+    },
+    {
+      "epoch": 0.08,
+      "learning_rate": 0.00023,
+      "loss": 0.7237,
+      "step": 170
+    },
+    {
+      "epoch": 0.08,
+      "learning_rate": 0.00021999999999999995,
+      "loss": 0.6205,
+      "step": 180
+    },
+    {
+      "epoch": 0.08,
+      "eval_loss": 0.63532555103302,
+      "eval_runtime": 172.3005,
+      "eval_samples_per_second": 45.606,
+      "eval_steps_per_second": 5.705,
+      "step": 180
+    },
+    {
+      "epoch": 0.09,
+      "learning_rate": 0.00020999999999999998,
+      "loss": 0.5346,
+      "step": 190
+    },
+    {
+      "epoch": 0.09,
+      "learning_rate": 0.00019999999999999998,
+      "loss": 0.4467,
+      "step": 200
+    },
+    {
+      "epoch": 0.09,
+      "eval_loss": 0.6415661573410034,
+      "eval_runtime": 172.5689,
+      "eval_samples_per_second": 45.535,
+      "eval_steps_per_second": 5.696,
+      "step": 200
+    },
+    {
+      "epoch": 0.1,
+      "learning_rate": 0.00018999999999999998,
+      "loss": 0.8274,
+      "step": 210
+    },
+    {
+      "epoch": 0.1,
+      "learning_rate": 0.00017999999999999998,
+      "loss": 0.689,
+      "step": 220
+    },
+    {
+      "epoch": 0.1,
+      "eval_loss": 0.6247297525405884,
+      "eval_runtime": 172.7326,
+      "eval_samples_per_second": 45.492,
+      "eval_steps_per_second": 5.691,
+      "step": 220
+    },
+    {
+      "epoch": 0.1,
+      "learning_rate": 0.00016999999999999999,
+      "loss": 0.6195,
+      "step": 230
+    },
+    {
+      "epoch": 0.11,
+      "learning_rate": 0.00015999999999999999,
+      "loss": 0.5187,
+      "step": 240
+    },
+    {
+      "epoch": 0.11,
+      "eval_loss": 0.6187988519668579,
+      "eval_runtime": 172.5129,
+      "eval_samples_per_second": 45.55,
+      "eval_steps_per_second": 5.698,
+      "step": 240
+    },
+    {
+      "epoch": 0.11,
+      "learning_rate": 0.00015,
+      "loss": 0.4326,
+      "step": 250
+    },
+    {
+      "epoch": 0.12,
+      "learning_rate": 0.00014,
+      "loss": 0.8144,
+      "step": 260
+    },
+    {
+      "epoch": 0.12,
+      "eval_loss": 0.6190418004989624,
+      "eval_runtime": 173.1094,
+      "eval_samples_per_second": 45.393,
+      "eval_steps_per_second": 5.678,
+      "step": 260
+    },
+    {
+      "epoch": 0.12,
+      "learning_rate": 0.00013,
+      "loss": 0.6642,
+      "step": 270
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 0.00011999999999999999,
+      "loss": 0.5946,
+      "step": 280
+    },
+    {
+      "epoch": 0.13,
+      "eval_loss": 0.6081172227859497,
+      "eval_runtime": 172.463,
+      "eval_samples_per_second": 45.563,
+      "eval_steps_per_second": 5.7,
+      "step": 280
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 0.00010999999999999998,
+      "loss": 0.515,
+      "step": 290
+    },
+    {
+      "epoch": 0.14,
+      "learning_rate": 9.999999999999999e-05,
+      "loss": 0.4127,
+      "step": 300
+    },
+    {
+      "epoch": 0.14,
+      "eval_loss": 0.622405469417572,
+      "eval_runtime": 172.9603,
+      "eval_samples_per_second": 45.432,
+      "eval_steps_per_second": 5.683,
+      "step": 300
+    },
+    {
+      "epoch": 0.14,
+      "learning_rate": 8.999999999999999e-05,
+      "loss": 0.8053,
+      "step": 310
+    },
+    {
+      "epoch": 0.14,
+      "learning_rate": 7.999999999999999e-05,
+      "loss": 0.6842,
+      "step": 320
+    },
+    {
+      "epoch": 0.14,
+      "eval_loss": 0.6062848567962646,
+      "eval_runtime": 172.4692,
+      "eval_samples_per_second": 45.562,
+      "eval_steps_per_second": 5.7,
+      "step": 320
+    },
+    {
+      "epoch": 0.15,
+      "learning_rate": 7e-05,
+      "loss": 0.5868,
+      "step": 330
+    },
+    {
+      "epoch": 0.15,
+      "learning_rate": 5.9999999999999995e-05,
+      "loss": 0.5091,
+      "step": 340
+    },
+    {
+      "epoch": 0.15,
+      "eval_loss": 0.6016470193862915,
+      "eval_runtime": 172.4602,
+      "eval_samples_per_second": 45.564,
+      "eval_steps_per_second": 5.7,
+      "step": 340
+    },
+    {
+      "epoch": 0.16,
+      "learning_rate": 4.9999999999999996e-05,
+      "loss": 0.4201,
+      "step": 350
+    },
+    {
+      "epoch": 0.16,
+      "learning_rate": 3.9999999999999996e-05,
+      "loss": 0.7834,
+      "step": 360
+    },
+    {
+      "epoch": 0.16,
+      "eval_loss": 0.6014373302459717,
+      "eval_runtime": 172.2045,
+      "eval_samples_per_second": 45.632,
+      "eval_steps_per_second": 5.708,
+      "step": 360
+    },
+    {
+      "epoch": 0.17,
+      "learning_rate": 2.9999999999999997e-05,
+      "loss": 0.6635,
+      "step": 370
+    },
+    {
+      "epoch": 0.17,
+      "learning_rate": 1.9999999999999998e-05,
+      "loss": 0.5875,
+      "step": 380
+    },
+    {
+      "epoch": 0.17,
+      "eval_loss": 0.5969696044921875,
+      "eval_runtime": 172.1021,
+      "eval_samples_per_second": 45.659,
+      "eval_steps_per_second": 5.712,
+      "step": 380
+    },
+    {
+      "epoch": 0.18,
+      "learning_rate": 9.999999999999999e-06,
+      "loss": 0.4966,
+      "step": 390
+    },
+    {
+      "epoch": 0.18,
+      "learning_rate": 0.0,
+      "loss": 0.4273,
+      "step": 400
+    },
+    {
+      "epoch": 0.18,
+      "eval_loss": 0.5965555906295776,
+      "eval_runtime": 172.4595,
+      "eval_samples_per_second": 45.564,
+      "eval_steps_per_second": 5.7,
+      "step": 400
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 400,
+  "num_train_epochs": 1,
+  "save_steps": 20,
+  "total_flos": 1.346139374616576e+16,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14414b5b5c958f41182877067baf415d391eb6c3646ab0774b3e5ce23b8178e8
+size 4600