Upload 8 files

README.md

@@ -1,3 +1,202 @@
 ---
-license: apache-2.0
+library_name: peft
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
 ---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.10.1.dev0

adapter_config.json

@@ -0,0 +1,35 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+  "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": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "q_proj",
+    "down_proj",
+    "up_proj",
+    "o_proj",
+    "lm_head",
+    "gate_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3bea70c23840fe6501cad72a02b862cf2e250731f702847898b818f1c1a3b203
+size 288506496

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5080dca898ff34d23bf644b3b88424f4a4bc1b7fc2eab083cbb0dd6a05aa53fa
+size 14048020

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:99eb85eda4049dc5426c772f8211476f668829df504297a3974de81043a518fb
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb7abe03cc0693b70973abe46c8e4fdcf77aa4dfb9543ba6f6e0984b3856055b
+size 1064

trainer_state.json

@@ -0,0 +1,471 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 33.333333333333336,
+  "eval_steps": 50,
+  "global_step": 1500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.1111111111111112,
+      "grad_norm": 2.6699063777923584,
+      "learning_rate": 2.443609022556391e-05,
+      "loss": 1.8217,
+      "step": 50
+    },
+    {
+      "epoch": 1.1111111111111112,
+      "eval_loss": 1.0424705743789673,
+      "eval_runtime": 4.0916,
+      "eval_samples_per_second": 43.993,
+      "eval_steps_per_second": 5.621,
+      "step": 50
+    },
+    {
+      "epoch": 2.2222222222222223,
+      "grad_norm": 0.44133517146110535,
+      "learning_rate": 2.380952380952381e-05,
+      "loss": 0.5439,
+      "step": 100
+    },
+    {
+      "epoch": 2.2222222222222223,
+      "eval_loss": 0.3811015784740448,
+      "eval_runtime": 4.0749,
+      "eval_samples_per_second": 44.173,
+      "eval_steps_per_second": 5.644,
+      "step": 100
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 0.540984034538269,
+      "learning_rate": 2.3182957393483708e-05,
+      "loss": 0.3496,
+      "step": 150
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 0.3363141715526581,
+      "eval_runtime": 4.089,
+      "eval_samples_per_second": 44.02,
+      "eval_steps_per_second": 5.625,
+      "step": 150
+    },
+    {
+      "epoch": 4.444444444444445,
+      "grad_norm": 0.4714152216911316,
+      "learning_rate": 2.255639097744361e-05,
+      "loss": 0.3178,
+      "step": 200
+    },
+    {
+      "epoch": 4.444444444444445,
+      "eval_loss": 0.3166368007659912,
+      "eval_runtime": 4.0511,
+      "eval_samples_per_second": 44.432,
+      "eval_steps_per_second": 5.677,
+      "step": 200
+    },
+    {
+      "epoch": 5.555555555555555,
+      "grad_norm": 0.5102563500404358,
+      "learning_rate": 2.1929824561403507e-05,
+      "loss": 0.2971,
+      "step": 250
+    },
+    {
+      "epoch": 5.555555555555555,
+      "eval_loss": 0.304388165473938,
+      "eval_runtime": 4.0541,
+      "eval_samples_per_second": 44.399,
+      "eval_steps_per_second": 5.673,
+      "step": 250
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 0.8356263041496277,
+      "learning_rate": 2.130325814536341e-05,
+      "loss": 0.2825,
+      "step": 300
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 0.29874512553215027,
+      "eval_runtime": 4.0506,
+      "eval_samples_per_second": 44.438,
+      "eval_steps_per_second": 5.678,
+      "step": 300
+    },
+    {
+      "epoch": 7.777777777777778,
+      "grad_norm": 0.694858968257904,
+      "learning_rate": 2.067669172932331e-05,
+      "loss": 0.2714,
+      "step": 350
+    },
+    {
+      "epoch": 7.777777777777778,
+      "eval_loss": 0.2942558825016022,
+      "eval_runtime": 4.074,
+      "eval_samples_per_second": 44.182,
+      "eval_steps_per_second": 5.646,
+      "step": 350
+    },
+    {
+      "epoch": 8.88888888888889,
+      "grad_norm": 0.7505309581756592,
+      "learning_rate": 2.0050125313283208e-05,
+      "loss": 0.2616,
+      "step": 400
+    },
+    {
+      "epoch": 8.88888888888889,
+      "eval_loss": 0.29128891229629517,
+      "eval_runtime": 4.0871,
+      "eval_samples_per_second": 44.041,
+      "eval_steps_per_second": 5.627,
+      "step": 400
+    },
+    {
+      "epoch": 10.0,
+      "grad_norm": 0.7603775858879089,
+      "learning_rate": 1.942355889724311e-05,
+      "loss": 0.2552,
+      "step": 450
+    },
+    {
+      "epoch": 10.0,
+      "eval_loss": 0.28786608576774597,
+      "eval_runtime": 4.052,
+      "eval_samples_per_second": 44.422,
+      "eval_steps_per_second": 5.676,
+      "step": 450
+    },
+    {
+      "epoch": 11.11111111111111,
+      "grad_norm": 0.831240177154541,
+      "learning_rate": 1.8796992481203007e-05,
+      "loss": 0.2472,
+      "step": 500
+    },
+    {
+      "epoch": 11.11111111111111,
+      "eval_loss": 0.28864821791648865,
+      "eval_runtime": 4.0371,
+      "eval_samples_per_second": 44.586,
+      "eval_steps_per_second": 5.697,
+      "step": 500
+    },
+    {
+      "epoch": 12.222222222222221,
+      "grad_norm": 0.7524340152740479,
+      "learning_rate": 1.8170426065162908e-05,
+      "loss": 0.2388,
+      "step": 550
+    },
+    {
+      "epoch": 12.222222222222221,
+      "eval_loss": 0.28881773352622986,
+      "eval_runtime": 4.0933,
+      "eval_samples_per_second": 43.974,
+      "eval_steps_per_second": 5.619,
+      "step": 550
+    },
+    {
+      "epoch": 13.333333333333334,
+      "grad_norm": 0.8262473940849304,
+      "learning_rate": 1.7543859649122806e-05,
+      "loss": 0.2309,
+      "step": 600
+    },
+    {
+      "epoch": 13.333333333333334,
+      "eval_loss": 0.2914719581604004,
+      "eval_runtime": 4.0773,
+      "eval_samples_per_second": 44.147,
+      "eval_steps_per_second": 5.641,
+      "step": 600
+    },
+    {
+      "epoch": 14.444444444444445,
+      "grad_norm": 0.8302382826805115,
+      "learning_rate": 1.6917293233082707e-05,
+      "loss": 0.2263,
+      "step": 650
+    },
+    {
+      "epoch": 14.444444444444445,
+      "eval_loss": 0.2899852395057678,
+      "eval_runtime": 4.0443,
+      "eval_samples_per_second": 44.507,
+      "eval_steps_per_second": 5.687,
+      "step": 650
+    },
+    {
+      "epoch": 15.555555555555555,
+      "grad_norm": 0.957399845123291,
+      "learning_rate": 1.6290726817042605e-05,
+      "loss": 0.2181,
+      "step": 700
+    },
+    {
+      "epoch": 15.555555555555555,
+      "eval_loss": 0.29406097531318665,
+      "eval_runtime": 4.0913,
+      "eval_samples_per_second": 43.996,
+      "eval_steps_per_second": 5.622,
+      "step": 700
+    },
+    {
+      "epoch": 16.666666666666668,
+      "grad_norm": 1.0171995162963867,
+      "learning_rate": 1.5664160401002506e-05,
+      "loss": 0.2115,
+      "step": 750
+    },
+    {
+      "epoch": 16.666666666666668,
+      "eval_loss": 0.2935585081577301,
+      "eval_runtime": 4.0514,
+      "eval_samples_per_second": 44.429,
+      "eval_steps_per_second": 5.677,
+      "step": 750
+    },
+    {
+      "epoch": 17.77777777777778,
+      "grad_norm": 0.9579535722732544,
+      "learning_rate": 1.5037593984962406e-05,
+      "loss": 0.2056,
+      "step": 800
+    },
+    {
+      "epoch": 17.77777777777778,
+      "eval_loss": 0.2986494302749634,
+      "eval_runtime": 4.0426,
+      "eval_samples_per_second": 44.526,
+      "eval_steps_per_second": 5.689,
+      "step": 800
+    },
+    {
+      "epoch": 18.88888888888889,
+      "grad_norm": 1.0283973217010498,
+      "learning_rate": 1.4411027568922305e-05,
+      "loss": 0.1983,
+      "step": 850
+    },
+    {
+      "epoch": 18.88888888888889,
+      "eval_loss": 0.30257824063301086,
+      "eval_runtime": 4.0596,
+      "eval_samples_per_second": 44.339,
+      "eval_steps_per_second": 5.666,
+      "step": 850
+    },
+    {
+      "epoch": 20.0,
+      "grad_norm": 1.068368673324585,
+      "learning_rate": 1.3784461152882205e-05,
+      "loss": 0.1915,
+      "step": 900
+    },
+    {
+      "epoch": 20.0,
+      "eval_loss": 0.30601659417152405,
+      "eval_runtime": 4.0465,
+      "eval_samples_per_second": 44.483,
+      "eval_steps_per_second": 5.684,
+      "step": 900
+    },
+    {
+      "epoch": 21.11111111111111,
+      "grad_norm": 0.987966001033783,
+      "learning_rate": 1.3157894736842106e-05,
+      "loss": 0.1834,
+      "step": 950
+    },
+    {
+      "epoch": 21.11111111111111,
+      "eval_loss": 0.3163508176803589,
+      "eval_runtime": 4.0462,
+      "eval_samples_per_second": 44.486,
+      "eval_steps_per_second": 5.684,
+      "step": 950
+    },
+    {
+      "epoch": 22.22222222222222,
+      "grad_norm": 1.046950101852417,
+      "learning_rate": 1.2531328320802006e-05,
+      "loss": 0.1773,
+      "step": 1000
+    },
+    {
+      "epoch": 22.22222222222222,
+      "eval_loss": 0.32225680351257324,
+      "eval_runtime": 4.0814,
+      "eval_samples_per_second": 44.102,
+      "eval_steps_per_second": 5.635,
+      "step": 1000
+    },
+    {
+      "epoch": 23.333333333333332,
+      "grad_norm": 1.2292746305465698,
+      "learning_rate": 1.1904761904761905e-05,
+      "loss": 0.1707,
+      "step": 1050
+    },
+    {
+      "epoch": 23.333333333333332,
+      "eval_loss": 0.3270200490951538,
+      "eval_runtime": 4.0696,
+      "eval_samples_per_second": 44.23,
+      "eval_steps_per_second": 5.652,
+      "step": 1050
+    },
+    {
+      "epoch": 24.444444444444443,
+      "grad_norm": 1.107651948928833,
+      "learning_rate": 1.1278195488721805e-05,
+      "loss": 0.1641,
+      "step": 1100
+    },
+    {
+      "epoch": 24.444444444444443,
+      "eval_loss": 0.3326013684272766,
+      "eval_runtime": 4.0592,
+      "eval_samples_per_second": 44.343,
+      "eval_steps_per_second": 5.666,
+      "step": 1100
+    },
+    {
+      "epoch": 25.555555555555557,
+      "grad_norm": 1.3203223943710327,
+      "learning_rate": 1.0651629072681704e-05,
+      "loss": 0.1575,
+      "step": 1150
+    },
+    {
+      "epoch": 25.555555555555557,
+      "eval_loss": 0.33997443318367004,
+      "eval_runtime": 4.0804,
+      "eval_samples_per_second": 44.113,
+      "eval_steps_per_second": 5.637,
+      "step": 1150
+    },
+    {
+      "epoch": 26.666666666666668,
+      "grad_norm": 1.2884823083877563,
+      "learning_rate": 1.0025062656641604e-05,
+      "loss": 0.1517,
+      "step": 1200
+    },
+    {
+      "epoch": 26.666666666666668,
+      "eval_loss": 0.3428906202316284,
+      "eval_runtime": 4.0803,
+      "eval_samples_per_second": 44.114,
+      "eval_steps_per_second": 5.637,
+      "step": 1200
+    },
+    {
+      "epoch": 27.77777777777778,
+      "grad_norm": 1.4833685159683228,
+      "learning_rate": 9.398496240601503e-06,
+      "loss": 0.1442,
+      "step": 1250
+    },
+    {
+      "epoch": 27.77777777777778,
+      "eval_loss": 0.35523876547813416,
+      "eval_runtime": 4.0449,
+      "eval_samples_per_second": 44.5,
+      "eval_steps_per_second": 5.686,
+      "step": 1250
+    },
+    {
+      "epoch": 28.88888888888889,
+      "grad_norm": 1.4259836673736572,
+      "learning_rate": 8.771929824561403e-06,
+      "loss": 0.1397,
+      "step": 1300
+    },
+    {
+      "epoch": 28.88888888888889,
+      "eval_loss": 0.36296555399894714,
+      "eval_runtime": 4.0386,
+      "eval_samples_per_second": 44.57,
+      "eval_steps_per_second": 5.695,
+      "step": 1300
+    },
+    {
+      "epoch": 30.0,
+      "grad_norm": 1.5832905769348145,
+      "learning_rate": 8.145363408521302e-06,
+      "loss": 0.1345,
+      "step": 1350
+    },
+    {
+      "epoch": 30.0,
+      "eval_loss": 0.3718196153640747,
+      "eval_runtime": 4.0526,
+      "eval_samples_per_second": 44.416,
+      "eval_steps_per_second": 5.675,
+      "step": 1350
+    },
+    {
+      "epoch": 31.11111111111111,
+      "grad_norm": 1.5873230695724487,
+      "learning_rate": 7.518796992481203e-06,
+      "loss": 0.1289,
+      "step": 1400
+    },
+    {
+      "epoch": 31.11111111111111,
+      "eval_loss": 0.38369277119636536,
+      "eval_runtime": 4.0471,
+      "eval_samples_per_second": 44.476,
+      "eval_steps_per_second": 5.683,
+      "step": 1400
+    },
+    {
+      "epoch": 32.22222222222222,
+      "grad_norm": 1.3492352962493896,
+      "learning_rate": 6.892230576441102e-06,
+      "loss": 0.1234,
+      "step": 1450
+    },
+    {
+      "epoch": 32.22222222222222,
+      "eval_loss": 0.39153799414634705,
+      "eval_runtime": 4.0507,
+      "eval_samples_per_second": 44.436,
+      "eval_steps_per_second": 5.678,
+      "step": 1450
+    },
+    {
+      "epoch": 33.333333333333336,
+      "grad_norm": 1.5531470775604248,
+      "learning_rate": 6.265664160401003e-06,
+      "loss": 0.1194,
+      "step": 1500
+    },
+    {
+      "epoch": 33.333333333333336,
+      "eval_loss": 0.3885114789009094,
+      "eval_runtime": 4.0759,
+      "eval_samples_per_second": 44.162,
+      "eval_steps_per_second": 5.643,
+      "step": 1500
+    }
+  ],
+  "logging_steps": 50,
+  "max_steps": 2000,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 45,
+  "save_steps": 25,
+  "total_flos": 3.996628758124954e+16,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:31fb09a8ca46eab683c0c509a96068143a53814b2d3e954b809726f49a16ece0
+size 4984