Checkpoint 3 at step 3000

checkpoint-3000/README.md

@@ -0,0 +1,204 @@
+---
+library_name: peft
+base_model: google-t5/t5-base
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+### Framework versions
+
+- PEFT 0.7.0

checkpoint-3000/adapter_config.json

@@ -0,0 +1,26 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google-t5/t5-base",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v",
+    "q"
+  ],
+  "task_type": "SEQ_2_SEQ_LM"
+}

checkpoint-3000/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d1800d7755dad7cc3e40c3741acc7b918a441c2d1dfea31a6e56efcf4081a094
+size 7098016

checkpoint-3000/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:74c2469bbe7f45a52b3e15a7bd4b6235ed1cad3192602010536a3ae43528459b
+size 14277259

checkpoint-3000/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b77e06d9e8a9ec437ce19bad2fcf9c3fc37002aceb56c45b0d6882f78fb7fc88
+size 14645

checkpoint-3000/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:991fcba719acec99b5539d96fcc576240d1d3bb15cabef2962124555f60c56e9
+size 1465

checkpoint-3000/trainer_state.json

@@ -0,0 +1,405 @@
+{
+  "best_metric": 0.5003042221069336,
+  "best_model_checkpoint": "./t5_checkpoints_full/checkpoint-1000",
+  "epoch": 0.4704775346977182,
+  "eval_steps": 1000,
+  "global_step": 3000,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.01,
+      "learning_rate": 2.88e-05,
+      "loss": 12.5022,
+      "step": 50
+    },
+    {
+      "epoch": 0.02,
+      "learning_rate": 5.82e-05,
+      "loss": 10.3469,
+      "step": 100
+    },
+    {
+      "epoch": 0.02,
+      "learning_rate": 8.819999999999999e-05,
+      "loss": 4.02,
+      "step": 150
+    },
+    {
+      "epoch": 0.03,
+      "learning_rate": 0.0001182,
+      "loss": 0.9201,
+      "step": 200
+    },
+    {
+      "epoch": 0.04,
+      "learning_rate": 0.0001482,
+      "loss": 0.7357,
+      "step": 250
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 0.00017699999999999997,
+      "loss": 0.6602,
+      "step": 300
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 0.00020699999999999996,
+      "loss": 0.6121,
+      "step": 350
+    },
+    {
+      "epoch": 0.06,
+      "learning_rate": 0.000237,
+      "loss": 0.5817,
+      "step": 400
+    },
+    {
+      "epoch": 0.07,
+      "learning_rate": 0.000267,
+      "loss": 0.5916,
+      "step": 450
+    },
+    {
+      "epoch": 0.08,
+      "learning_rate": 0.00029699999999999996,
+      "loss": 0.5675,
+      "step": 500
+    },
+    {
+      "epoch": 0.09,
+      "learning_rate": 0.0002992913893064204,
+      "loss": 0.57,
+      "step": 550
+    },
+    {
+      "epoch": 0.09,
+      "learning_rate": 0.0002984861498818982,
+      "loss": 0.561,
+      "step": 600
+    },
+    {
+      "epoch": 0.1,
+      "learning_rate": 0.000297680910457376,
+      "loss": 0.5669,
+      "step": 650
+    },
+    {
+      "epoch": 0.11,
+      "learning_rate": 0.00029687567103285373,
+      "loss": 0.5659,
+      "step": 700
+    },
+    {
+      "epoch": 0.12,
+      "learning_rate": 0.0002960704316083315,
+      "loss": 0.5673,
+      "step": 750
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 0.0002952651921838093,
+      "loss": 0.5619,
+      "step": 800
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 0.00029449216233626795,
+      "loss": 0.5719,
+      "step": 850
+    },
+    {
+      "epoch": 0.14,
+      "learning_rate": 0.00029368692291174576,
+      "loss": 0.5576,
+      "step": 900
+    },
+    {
+      "epoch": 0.15,
+      "learning_rate": 0.0002928816834872235,
+      "loss": 0.5567,
+      "step": 950
+    },
+    {
+      "epoch": 0.16,
+      "learning_rate": 0.00029210865363968216,
+      "loss": 0.5597,
+      "step": 1000
+    },
+    {
+      "epoch": 0.16,
+      "eval_loss": 0.5003042221069336,
+      "eval_runtime": 95.3235,
+      "eval_samples_per_second": 118.879,
+      "eval_steps_per_second": 7.438,
+      "step": 1000
+    },
+    {
+      "epoch": 0.16,
+      "learning_rate": 0.0002913195190036504,
+      "loss": 0.5565,
+      "step": 1050
+    },
+    {
+      "epoch": 0.17,
+      "learning_rate": 0.00029057869873308994,
+      "loss": 0.5767,
+      "step": 1100
+    },
+    {
+      "epoch": 0.18,
+      "learning_rate": 0.00028978956409705817,
+      "loss": 0.562,
+      "step": 1150
+    },
+    {
+      "epoch": 0.19,
+      "learning_rate": 0.0002890004294610264,
+      "loss": 0.5864,
+      "step": 1200
+    },
+    {
+      "epoch": 0.2,
+      "learning_rate": 0.00028819519003650415,
+      "loss": 0.626,
+      "step": 1250
+    },
+    {
+      "epoch": 0.2,
+      "learning_rate": 0.0002873899506119819,
+      "loss": 0.7742,
+      "step": 1300
+    },
+    {
+      "epoch": 0.21,
+      "learning_rate": 0.0002866169207644406,
+      "loss": 1.1101,
+      "step": 1350
+    },
+    {
+      "epoch": 0.22,
+      "learning_rate": 0.00028581168133991837,
+      "loss": 1.3211,
+      "step": 1400
+    },
+    {
+      "epoch": 0.23,
+      "learning_rate": 0.0002850064419153961,
+      "loss": 1.413,
+      "step": 1450
+    },
+    {
+      "epoch": 0.24,
+      "learning_rate": 0.00028420120249087393,
+      "loss": 1.4265,
+      "step": 1500
+    },
+    {
+      "epoch": 0.24,
+      "learning_rate": 0.0002834281726433326,
+      "loss": 1.47,
+      "step": 1550
+    },
+    {
+      "epoch": 0.25,
+      "learning_rate": 0.00028262293321881034,
+      "loss": 1.4561,
+      "step": 1600
+    },
+    {
+      "epoch": 0.26,
+      "learning_rate": 0.0002818337985827786,
+      "loss": 1.4693,
+      "step": 1650
+    },
+    {
+      "epoch": 0.27,
+      "learning_rate": 0.0002810285591582563,
+      "loss": 1.4729,
+      "step": 1700
+    },
+    {
+      "epoch": 0.27,
+      "learning_rate": 0.00028022331973373413,
+      "loss": 1.4599,
+      "step": 1750
+    },
+    {
+      "epoch": 0.28,
+      "learning_rate": 0.0002794180803092119,
+      "loss": 1.4725,
+      "step": 1800
+    },
+    {
+      "epoch": 0.29,
+      "learning_rate": 0.0002786128408846897,
+      "loss": 1.4503,
+      "step": 1850
+    },
+    {
+      "epoch": 0.3,
+      "learning_rate": 0.0002778237062486579,
+      "loss": 1.4812,
+      "step": 1900
+    },
+    {
+      "epoch": 0.31,
+      "learning_rate": 0.0002770184668241357,
+      "loss": 1.4761,
+      "step": 1950
+    },
+    {
+      "epoch": 0.31,
+      "learning_rate": 0.00027621322739961344,
+      "loss": 1.496,
+      "step": 2000
+    },
+    {
+      "epoch": 0.31,
+      "eval_loss": 1.251204252243042,
+      "eval_runtime": 94.8348,
+      "eval_samples_per_second": 119.492,
+      "eval_steps_per_second": 7.476,
+      "step": 2000
+    },
+    {
+      "epoch": 0.32,
+      "learning_rate": 0.00027542409276358167,
+      "loss": 1.4488,
+      "step": 2050
+    },
+    {
+      "epoch": 0.33,
+      "learning_rate": 0.00027461885333905943,
+      "loss": 1.455,
+      "step": 2100
+    },
+    {
+      "epoch": 0.34,
+      "learning_rate": 0.00027381361391453724,
+      "loss": 1.4353,
+      "step": 2150
+    },
+    {
+      "epoch": 0.35,
+      "learning_rate": 0.000273008374490015,
+      "loss": 1.4524,
+      "step": 2200
+    },
+    {
+      "epoch": 0.35,
+      "learning_rate": 0.0002722192398539832,
+      "loss": 1.4701,
+      "step": 2250
+    },
+    {
+      "epoch": 0.36,
+      "learning_rate": 0.000271414000429461,
+      "loss": 1.4734,
+      "step": 2300
+    },
+    {
+      "epoch": 0.37,
+      "learning_rate": 0.0002706409705819197,
+      "loss": 1.5035,
+      "step": 2350
+    },
+    {
+      "epoch": 0.38,
+      "learning_rate": 0.00026983573115739744,
+      "loss": 1.4513,
+      "step": 2400
+    },
+    {
+      "epoch": 0.38,
+      "learning_rate": 0.00026904659652136567,
+      "loss": 1.4641,
+      "step": 2450
+    },
+    {
+      "epoch": 0.39,
+      "learning_rate": 0.0002682413570968434,
+      "loss": 1.4585,
+      "step": 2500
+    },
+    {
+      "epoch": 0.4,
+      "learning_rate": 0.00026743611767232123,
+      "loss": 1.4673,
+      "step": 2550
+    },
+    {
+      "epoch": 0.41,
+      "learning_rate": 0.0002666469830362894,
+      "loss": 1.4671,
+      "step": 2600
+    },
+    {
+      "epoch": 0.42,
+      "learning_rate": 0.0002658578484002577,
+      "loss": 1.4702,
+      "step": 2650
+    },
+    {
+      "epoch": 0.42,
+      "learning_rate": 0.00026508481855271634,
+      "loss": 1.4612,
+      "step": 2700
+    },
+    {
+      "epoch": 0.43,
+      "learning_rate": 0.0002642956839166845,
+      "loss": 1.4713,
+      "step": 2750
+    },
+    {
+      "epoch": 0.44,
+      "learning_rate": 0.00026350654928065275,
+      "loss": 1.4573,
+      "step": 2800
+    },
+    {
+      "epoch": 0.45,
+      "learning_rate": 0.000262717414644621,
+      "loss": 1.4586,
+      "step": 2850
+    },
+    {
+      "epoch": 0.45,
+      "learning_rate": 0.00026191217522009873,
+      "loss": 1.4674,
+      "step": 2900
+    },
+    {
+      "epoch": 0.46,
+      "learning_rate": 0.00026110693579557654,
+      "loss": 1.4466,
+      "step": 2950
+    },
+    {
+      "epoch": 0.47,
+      "learning_rate": 0.0002603339059480352,
+      "loss": 1.4897,
+      "step": 3000
+    },
+    {
+      "epoch": 0.47,
+      "eval_loss": 1.2417596578598022,
+      "eval_runtime": 94.8105,
+      "eval_samples_per_second": 119.523,
+      "eval_steps_per_second": 7.478,
+      "step": 3000
+    }
+  ],
+  "logging_steps": 50,
+  "max_steps": 19128,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 1000,
+  "total_flos": 5.8981796020224e+16,
+  "train_batch_size": 16,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-3000/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:020399f67c678641c05351df778629bde428b25cc882f50dae492e08cb9604ee
+size 5073

checkpoint-3000/training_metrics.json

@@ -0,0 +1,90 @@
+{
+  "step": 3000,
+  "epoch": 0.4704775346977182,
+  "best_eval_loss": 0.5003042221069336,
+  "checkpoint_number": 3,
+  "recent_metrics": [
+    {
+      "step": 2600,
+      "epoch": 0.41,
+      "loss": 1.4671,
+      "learning_rate": 0.0002666469830362894,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.7
+    },
+    {
+      "step": 2650,
+      "epoch": 0.42,
+      "loss": 1.4702,
+      "learning_rate": 0.0002658578484002577,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.7
+    },
+    {
+      "step": 2700,
+      "epoch": 0.42,
+      "loss": 1.4612,
+      "learning_rate": 0.00026508481855271634,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 2750,
+      "epoch": 0.43,
+      "loss": 1.4713,
+      "learning_rate": 0.0002642956839166845,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 2800,
+      "epoch": 0.44,
+      "loss": 1.4573,
+      "learning_rate": 0.00026350654928065275,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 2850,
+      "epoch": 0.45,
+      "loss": 1.4586,
+      "learning_rate": 0.000262717414644621,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 2900,
+      "epoch": 0.45,
+      "loss": 1.4674,
+      "learning_rate": 0.00026191217522009873,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 2950,
+      "epoch": 0.46,
+      "loss": 1.4466,
+      "learning_rate": 0.00026110693579557654,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 3000,
+      "epoch": 0.47,
+      "loss": 1.4897,
+      "learning_rate": 0.0002603339059480352,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.8
+    },
+    {
+      "step": 3000,
+      "epoch": 0.47,
+      "eval_loss": 1.2417596578598022,
+      "eval_runtime": 94.8105,
+      "eval_samples_per_second": 119.523,
+      "eval_steps_per_second": 7.478,
+      "gpu_memory_gb": 0.8661794662475586,
+      "system_memory_percent": 6.7
+    }
+  ]
+}