Instructions to use LEAP-LAB-KUS/jevkt-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LEAP-LAB-KUS/jevkt-checkpoints with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Pod D e28 checkpoints (E27 27B / E28 diversity / E29 / E30 arms)
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- e28/S1-E28-C0-syn/DONE +1 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter/README.md +206 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e28/S1-E28-C0-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e28/S1-E28-C0-syn/ckpt-16000/calibration.json +29 -0
- e28/S1-E28-C0-syn/ckpt-16000/head.safetensors +3 -0
- e28/S1-E28-C0-syn/ckpt-16000/judge_config.json +164 -0
- e28/S1-E28-C0-syn/train_log.jsonl +57 -0
- e28/S1-E28-E18A050-rt-syn/DONE +1 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/README.md +206 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/calibration.json +29 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/head.safetensors +3 -0
- e28/S1-E28-E18A050-rt-syn/ckpt-16000/judge_config.json +164 -0
- e28/S1-E28-E18A050-rt-syn/train_log.jsonl +57 -0
- e28/S1-E28-E18A100-rt-syn/DONE +1 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/README.md +206 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/calibration.json +29 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/head.safetensors +3 -0
- e28/S1-E28-E18A100-rt-syn/ckpt-16000/judge_config.json +164 -0
- e28/S1-E28-E18A100-rt-syn/train_log.jsonl +57 -0
- e28/S1-E28-E30-a1-rw-syn/DONE +1 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter/README.md +206 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/calibration.json +29 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/head.safetensors +3 -0
- e28/S1-E28-E30-a1-rw-syn/ckpt-16000/judge_config.json +164 -0
- e28/S1-E28-E30-a1-rw-syn/train_log.jsonl +57 -0
- e28/S1-E28-E30-a1-uni-syn/DONE +1 -0
- e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/README.md +206 -0
- e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
e28/S1-E28-C0-syn/DONE
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e28/S1-E28-C0-syn/ckpt-16000/adapter/README.md
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| 1 |
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---
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| 2 |
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base_model: /workspace/jev_kt/models/hf/JEV-9B
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library_name: peft
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tags:
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- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
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- lora
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- transformers
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| 8 |
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---
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| 9 |
+
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| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
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| 15 |
+
|
| 16 |
+
## Model Details
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| 17 |
+
|
| 18 |
+
### Model Description
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| 19 |
+
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| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
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| 25 |
+
- **Funded by [optional]:** [More Information Needed]
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| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
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[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
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|
| 60 |
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[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
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| 63 |
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|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
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| 66 |
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[More Information Needed]
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| 67 |
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|
| 68 |
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### Recommendations
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| 69 |
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| 70 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 71 |
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| 72 |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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| 73 |
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| 74 |
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## How to Get Started with the Model
|
| 75 |
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| 76 |
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Use the code below to get started with the model.
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| 77 |
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| 78 |
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[More Information Needed]
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| 80 |
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## Training Details
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| 81 |
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| 82 |
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### Training Data
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| 83 |
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| 84 |
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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| 98 |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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| 106 |
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## Evaluation
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| 108 |
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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| 112 |
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#### Testing Data
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| 114 |
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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| 118 |
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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| 124 |
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#### Metrics
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| 126 |
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| 127 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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| 132 |
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[More Information Needed]
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#### Summary
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| 136 |
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## Model Examination [optional]
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| 140 |
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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| 144 |
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## Environmental Impact
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| 146 |
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| 147 |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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| 148 |
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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).
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| 150 |
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| 151 |
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- **Hardware Type:** [More Information Needed]
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| 152 |
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- **Hours used:** [More Information Needed]
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| 153 |
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- **Cloud Provider:** [More Information Needed]
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| 154 |
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- **Compute Region:** [More Information Needed]
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| 155 |
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- **Carbon Emitted:** [More Information Needed]
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| 156 |
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## Technical Specifications [optional]
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| 158 |
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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| 164 |
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[More Information Needed]
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| 166 |
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#### Hardware
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| 168 |
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[More Information Needed]
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#### Software
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| 172 |
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[More Information Needed]
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| 174 |
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## Citation [optional]
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| 176 |
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| 177 |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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| 178 |
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**BibTeX:**
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[More Information Needed]
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| 183 |
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**APA:**
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| 184 |
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| 185 |
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[More Information Needed]
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| 186 |
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| 187 |
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## Glossary [optional]
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| 188 |
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| 189 |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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| 190 |
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[More Information Needed]
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| 192 |
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## More Information [optional]
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| 194 |
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[More Information Needed]
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## Model Card Authors [optional]
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| 198 |
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[More Information Needed]
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## Model Card Contact
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| 202 |
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[More Information Needed]
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| 204 |
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### Framework versions
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| 205 |
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| 206 |
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- PEFT 0.21.2
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e28/S1-E28-C0-syn/ckpt-16000/adapter/adapter_config.json
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e28/S1-E28-C0-syn/ckpt-16000/adapter/adapter_model.safetensors
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ADDED
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e28/S1-E28-C0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
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size 176641832
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ADDED
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| 99 |
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|
e28/S1-E28-C0-syn/ckpt-16000/calibration.json
ADDED
|
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|
| 29 |
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|
e28/S1-E28-C0-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 3 |
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size 393464
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e28/S1-E28-C0-syn/ckpt-16000/judge_config.json
ADDED
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| 1 |
+
{
|
| 2 |
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"base_model_path": "/root/models/Qwen3.5-9B",
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| 3 |
+
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|
| 4 |
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| 6 |
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| 7 |
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| 9 |
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| 11 |
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| 13 |
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|
| 14 |
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| 15 |
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"choice": [
|
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| 17 |
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|
| 18 |
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]
|
| 19 |
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|
| 20 |
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"verbalizers": [
|
| 21 |
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"false",
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| 22 |
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| 23 |
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| 24 |
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|
| 26 |
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| 27 |
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| 28 |
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|
| 29 |
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|
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|
| 31 |
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| 32 |
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| 33 |
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"E",
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| 34 |
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"F",
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"G",
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"H",
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| 37 |
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"I",
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| 38 |
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"J",
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| 39 |
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"K",
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"L",
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"M",
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"N",
|
| 43 |
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"O",
|
| 44 |
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"P"
|
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46,
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47
|
| 73 |
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| 74 |
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| 75 |
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"noul",
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| 76 |
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"choice",
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| 77 |
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"score"
|
| 78 |
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],
|
| 79 |
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"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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"model_version": "0.8.0",
|
| 81 |
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"lm_head_included": true,
|
| 82 |
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| 83 |
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|
| 84 |
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"lora": {
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| 85 |
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"r": 16,
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| 86 |
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"lora_alpha": 32,
|
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"lora_dropout": 0.05,
|
| 88 |
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|
| 89 |
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"down_proj",
|
| 90 |
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"gate_proj",
|
| 91 |
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"in_proj_qkv",
|
| 92 |
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"in_proj_z",
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| 93 |
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"k_proj",
|
| 94 |
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"o_proj",
|
| 95 |
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"out_proj",
|
| 96 |
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"q_proj",
|
| 97 |
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"up_proj",
|
| 98 |
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"v_proj"
|
| 99 |
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| 100 |
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| 111 |
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|
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|
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|
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|
| 164 |
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|
e28/S1-E28-C0-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
+
{"time": "05:42:42", "event": "start", "data": "data/e19/E19-b-n16k", "data_manifest": {"arm": "E19-b-n16k", "name": null, "train_sha256": "9e31412d9aac0064859cdf9aae1636242d1a9dbfc3ab398a1f5ec10da1e7a50e", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 4.794634580612183}
|
| 2 |
+
{"time": "05:44:34", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 1742.0688985934723, "loss": 0.6418524533510208, "entropy": 0.6674938574433327, "sharp": 0.09449283499270678}
|
| 3 |
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{"time": "05:45:28", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 2276.391236296654, "loss": 0.6543252449482679, "entropy": 0.6451239045709372, "sharp": 0.11809633672237396}
|
| 4 |
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{"time": "05:46:27", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 2592.524926228113, "loss": 0.7097902707755566, "entropy": 0.6600528657436371, "sharp": 0.11035785730928183}
|
| 5 |
+
{"time": "05:47:22", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 2768.586496905704, "loss": 0.6805907804518938, "entropy": 0.6736207865178585, "sharp": 0.08694715239107609}
|
| 6 |
+
{"time": "05:48:18", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 2889.323608493551, "loss": 0.6551038809120655, "entropy": 0.6535464469343424, "sharp": 0.10296877473592758}
|
| 7 |
+
{"time": "05:49:14", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 2977.4619186367863, "loss": 0.6448147781193256, "entropy": 0.6451537758111954, "sharp": 0.12875191681087017}
|
| 8 |
+
{"time": "05:50:12", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 3036.6014164640724, "loss": 0.647441454231739, "entropy": 0.683087445795536, "sharp": 0.057668830268085}
|
| 9 |
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{"time": "05:51:08", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 3084.627950729468, "loss": 0.7112917471677065, "entropy": 0.637435607612133, "sharp": 0.1373877078294754}
|
| 10 |
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{"time": "05:52:04", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 3124.1413080678926, "loss": 0.6655900441110134, "entropy": 0.6652580164372921, "sharp": 0.10431478638201952}
|
| 11 |
+
{"time": "05:53:00", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 3152.110435086271, "loss": 0.6226409263908863, "entropy": 0.6681161969900131, "sharp": 0.09350143652409315}
|
| 12 |
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{"time": "05:53:25", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.6027932167053223, "noul_T": 0.8047402751192091, "noul_auc": 0.7031611280822265, "noul_acc": 0.688, "noul_f1": 0.75625, "noul_nll": 0.6076746896356344, "noul_ece": 0.06157691490650178, "noul_brier": 0.2100360241730981, "noul_sharp": 0.14764730632305145, "entropy": 0.6277173757553101}
|
| 13 |
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{"time": "05:54:23", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 3068.6206931182887, "loss": 0.684677317738533, "entropy": 0.6516259256750345, "sharp": 0.11634835135191679}
|
| 14 |
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{"time": "05:55:19", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 3089.830183059434, "loss": 0.6259176284074783, "entropy": 0.6395060457289219, "sharp": 0.14079864881932735}
|
| 15 |
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{"time": "05:56:16", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 3116.7881936735016, "loss": 0.6442239172756672, "entropy": 0.6784866154193878, "sharp": 0.06614390201866627}
|
| 16 |
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{"time": "05:57:14", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 3139.759900493683, "loss": 0.6844842508435249, "entropy": 0.64948820322752, "sharp": 0.13435495272278786}
|
| 17 |
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{"time": "05:58:09", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 3160.5145456206246, "loss": 0.6813701651990414, "entropy": 0.668898917734623, "sharp": 0.08269481174647808}
|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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{"time": "06:01:56", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 3223.8353887126264, "loss": 0.6503072865307331, "entropy": 0.6558262407779694, "sharp": 0.10804163292050362}
|
| 22 |
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|
| 23 |
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{"time": "06:03:13", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.625215470790863, "noul_T": 0.6322796617575723, "noul_auc": 0.7433798585677879, "noul_acc": 0.66, "noul_f1": 0.6875, "noul_nll": 0.6210226207077503, "noul_ece": 0.14127235460281373, "noul_brier": 0.21537573031776094, "noul_sharp": 0.11072076112031937, "entropy": 0.6588683724403381}
|
| 24 |
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{"time": "06:04:09", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 3195.1610605836995, "loss": 0.6731307283043861, "entropy": 0.6324892044067383, "sharp": 0.14314057677984238}
|
| 25 |
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{"time": "06:05:04", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 3207.7340288322866, "loss": 0.7052969560027122, "entropy": 0.6550907492637634, "sharp": 0.11679293122142553}
|
| 26 |
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{"time": "06:06:01", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 3218.423092980036, "loss": 0.6667746938765049, "entropy": 0.6606782749295235, "sharp": 0.10835204273462296}
|
| 27 |
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{"time": "06:06:58", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 3228.7448099209337, "loss": 0.6714807525277138, "entropy": 0.6531186066567898, "sharp": 0.11655727680772543}
|
| 28 |
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|
| 29 |
+
{"time": "06:08:50", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 3245.5095129602087, "loss": 0.653316430747509, "entropy": 0.6700648739933968, "sharp": 0.0919972499832511}
|
| 30 |
+
{"time": "06:09:49", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 3255.199106196958, "loss": 0.640799886547029, "entropy": 0.6467154920101166, "sharp": 0.13283592090010643}
|
| 31 |
+
{"time": "06:10:46", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 3262.485544814, "loss": 0.6944353505969048, "entropy": 0.6748707816004753, "sharp": 0.08099196664988995}
|
| 32 |
+
{"time": "06:11:43", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 3270.3215016883805, "loss": 0.6646610796451569, "entropy": 0.6652002595365047, "sharp": 0.0954577811062336}
|
| 33 |
+
{"time": "06:12:41", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 3276.736460884371, "loss": 0.6731904521584511, "entropy": 0.6602216698229313, "sharp": 0.11017826851457357}
|
| 34 |
+
{"time": "06:13:01", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.597034752368927, "noul_T": 0.6421206855787178, "noul_auc": 0.7323589475283117, "noul_acc": 0.718, "noul_f1": 0.7860394537177542, "noul_nll": 0.5973743291497231, "noul_ece": 0.08663646721839906, "noul_brier": 0.2042407758885801, "noul_sharp": 0.1332443803548813, "entropy": 0.6418294906616211}
|
| 35 |
+
{"time": "06:13:56", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 3247.7827177374384, "loss": 0.6042209938168526, "entropy": 0.6657007820904255, "sharp": 0.10047882981598377}
|
| 36 |
+
{"time": "06:14:53", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 3254.074569995877, "loss": 0.672166720032692, "entropy": 0.6612759456038475, "sharp": 0.09925397951155901}
|
| 37 |
+
{"time": "06:15:51", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 3260.7679436398503, "loss": 0.6972816735506058, "entropy": 0.643512986600399, "sharp": 0.12919290456920862}
|
| 38 |
+
{"time": "06:16:45", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 3266.4804837555394, "loss": 0.6724905520677567, "entropy": 0.6493063047528267, "sharp": 0.11664058640599251}
|
| 39 |
+
{"time": "06:17:42", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 3272.1660910371143, "loss": 0.6453768238425255, "entropy": 0.6563559770584106, "sharp": 0.11054976005107164}
|
| 40 |
+
{"time": "06:18:38", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 3277.0396115841886, "loss": 0.6560497954487801, "entropy": 0.635651208460331, "sharp": 0.14939494617283344}
|
| 41 |
+
{"time": "06:19:35", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 3282.9871352353107, "loss": 0.686661321669817, "entropy": 0.6401583924889565, "sharp": 0.13821567595005035}
|
| 42 |
+
{"time": "06:20:32", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 3287.3508514962205, "loss": 0.6733216270804405, "entropy": 0.6461369395256042, "sharp": 0.12509455811232328}
|
| 43 |
+
{"time": "06:21:29", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 3293.099189016152, "loss": 0.6431321948766708, "entropy": 0.6418887823820114, "sharp": 0.1216413863003254}
|
| 44 |
+
{"time": "06:22:23", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 3296.8323002762377, "loss": 0.6882326304912567, "entropy": 0.6303502470254898, "sharp": 0.14134303573518991}
|
| 45 |
+
{"time": "06:22:43", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5883752703666687, "noul_T": 0.8063948425248696, "noul_auc": 0.7352956068252012, "noul_acc": 0.722, "noul_f1": 0.7851622874806801, "noul_nll": 0.5876846368610859, "noul_ece": 0.05814056313037875, "noul_brier": 0.20021823288795024, "noul_sharp": 0.1605500727891922, "entropy": 0.6165220141410828}
|
| 46 |
+
{"time": "06:23:40", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 3273.217062149899, "loss": 0.6581775918602943, "entropy": 0.6659778021275997, "sharp": 0.09172998555004597}
|
| 47 |
+
{"time": "06:24:35", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 3278.0760739602315, "loss": 0.6624073907732964, "entropy": 0.6563186943531036, "sharp": 0.10841984767466784}
|
| 48 |
+
{"time": "06:25:33", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 3282.822632861716, "loss": 0.668071087449789, "entropy": 0.646204873919487, "sharp": 0.12354523129761219}
|
| 49 |
+
{"time": "06:26:29", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 3287.3099151168462, "loss": 0.6683605443686247, "entropy": 0.6525228191167116, "sharp": 0.11701337993144989}
|
| 50 |
+
{"time": "06:27:26", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 3291.6826129417955, "loss": 0.6479352544993162, "entropy": 0.6605901643633842, "sharp": 0.09802819322794676}
|
| 51 |
+
{"time": "06:28:22", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 3295.468233519694, "loss": 0.6506122052669525, "entropy": 0.6533954069018364, "sharp": 0.11456773895770311}
|
| 52 |
+
{"time": "06:29:20", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 3299.817314706129, "loss": 0.7218317352235317, "entropy": 0.6592727117240429, "sharp": 0.10681359004229307}
|
| 53 |
+
{"time": "06:30:16", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 3303.496486455061, "loss": 0.6903524547815323, "entropy": 0.6571662090718746, "sharp": 0.10609687305986881}
|
| 54 |
+
{"time": "06:31:10", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 3306.3984164704566, "loss": 0.5719492360949516, "entropy": 0.6424555853009224, "sharp": 0.13239238318055868}
|
| 55 |
+
{"time": "06:32:06", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 3309.895620939873, "loss": 0.6167443245649338, "entropy": 0.6454180404543877, "sharp": 0.12842741049826145}
|
| 56 |
+
{"time": "06:32:26", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5884483456611633, "noul_T": 0.798413540070553, "noul_auc": 0.7332534471992033, "noul_acc": 0.72, "noul_f1": 0.7859327217125383, "noul_nll": 0.5891514290720224, "noul_ece": 0.061191798210144054, "noul_brier": 0.200934913549001, "noul_sharp": 0.15952661633491516, "entropy": 0.6176946759223938}
|
| 57 |
+
{"time": "06:33:13", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9808867, "tok_per_s": 3237.0095425583345, "rows_per_s": 5.558003251258509, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5733858942985535, "noul_T": 0.8210398824005378, "choice_ce": 0.6707404851913452, "choice_T": 1.0076231342175517, "score_ce": 1.055969476699829, "score_T": 0.9955852301156168, "noul_auc": 0.7198933333333333, "noul_acc": 0.699, "noul_f1": 0.7794871794871795, "noul_nll": 0.5898938082531094, "noul_ece": 0.052008005946874616, "noul_brier": 0.20208435675807834, "noul_sharp": 0.1651003509759903, "entropy": 0.6122925281524658}, "dropped_long": 0, "peak_gib": 18.282634735107422}
|
e28/S1-E28-E18A050-rt-syn/DONE
ADDED
|
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| 1 |
+
2026-10-21 06:54:56
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/README.md
ADDED
|
@@ -0,0 +1,206 @@
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|
| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- 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. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
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).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
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"ensure_weight_tying": false,
|
| 13 |
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"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
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"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"o_proj",
|
| 39 |
+
"k_proj",
|
| 40 |
+
"in_proj_z",
|
| 41 |
+
"out_proj",
|
| 42 |
+
"q_proj",
|
| 43 |
+
"v_proj",
|
| 44 |
+
"up_proj",
|
| 45 |
+
"down_proj",
|
| 46 |
+
"in_proj_qkv",
|
| 47 |
+
"gate_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
+
"task_type": null,
|
| 51 |
+
"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
+
"use_dora": false,
|
| 54 |
+
"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
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oid sha256:5d32e8cade04cb62e764ce8960d6d4340906a030b264367825ba9b79963a9929
|
| 3 |
+
size 160486456
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
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|
|
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|
| 1 |
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{
|
| 2 |
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"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
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"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
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"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
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},
|
| 9 |
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"base_model_name_or_path": null,
|
| 10 |
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"bias": "none",
|
| 11 |
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|
| 12 |
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|
| 13 |
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"eva_config": null,
|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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"init_lora_weights": true,
|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
+
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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"lora_dropout": 0.0,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
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|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
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|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 32,
|
| 35 |
+
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|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"down_proj",
|
| 39 |
+
"gate_proj",
|
| 40 |
+
"in_proj_qkv",
|
| 41 |
+
"in_proj_z",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"lm_head",
|
| 44 |
+
"o_proj",
|
| 45 |
+
"out_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
+
"up_proj",
|
| 48 |
+
"v_proj"
|
| 49 |
+
],
|
| 50 |
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"target_parameters": null,
|
| 51 |
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"task_type": null,
|
| 52 |
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"trainable_token_indices": null,
|
| 53 |
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|
| 54 |
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|
| 55 |
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"use_qalora": false,
|
| 56 |
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"use_rslora": false,
|
| 57 |
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"velora_config": null
|
| 58 |
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}
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
|
|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:eb2307e1988ab4b5c8524539ee27ea8a645102f2a10ab1c486095071391da9a6
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| 3 |
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size 176641832
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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|
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0,
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2
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8
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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"3",
|
| 77 |
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"4",
|
| 78 |
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|
| 79 |
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"A",
|
| 80 |
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"B",
|
| 81 |
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"C",
|
| 82 |
+
"D",
|
| 83 |
+
"E",
|
| 84 |
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"F",
|
| 85 |
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"G",
|
| 86 |
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"H",
|
| 87 |
+
"I",
|
| 88 |
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"J",
|
| 89 |
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"K",
|
| 90 |
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"L",
|
| 91 |
+
"M",
|
| 92 |
+
"N",
|
| 93 |
+
"O",
|
| 94 |
+
"P"
|
| 95 |
+
],
|
| 96 |
+
"template_version": "bare-v1"
|
| 97 |
+
},
|
| 98 |
+
"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
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|
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|
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|
| 1 |
+
{
|
| 2 |
+
"version": 1,
|
| 3 |
+
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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"n": 1087,
|
| 11 |
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|
| 12 |
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|
| 13 |
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"ce_after": 0.5574237108230591
|
| 14 |
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|
| 15 |
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"choice": {
|
| 16 |
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"n": 60,
|
| 17 |
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|
| 18 |
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|
| 19 |
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"ce_after": 0.683573842048645
|
| 20 |
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|
| 21 |
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|
| 22 |
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"n": 53,
|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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},
|
| 28 |
+
"source": "models/e28/S1-E28-E18A050-rt-syn/ckpt-16000"
|
| 29 |
+
}
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:04f1e3aebba797e65e6f251cf88d134d9cb90ba13166ecaa4ef8d3113bfbdf1d
|
| 3 |
+
size 393464
|
e28/S1-E28-E18A050-rt-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"base_model_path": "/root/models/Qwen3.5-9B",
|
| 3 |
+
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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| 8 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
+
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|
| 14 |
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|
| 15 |
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"choice": [
|
| 16 |
+
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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"verbalizers": [
|
| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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|
| 26 |
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| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
+
"N",
|
| 43 |
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"O",
|
| 44 |
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"P"
|
| 45 |
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],
|
| 46 |
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"template_version": "bare-v1"
|
| 47 |
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},
|
| 48 |
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"verbalizer_ids": [
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| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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38,
|
| 64 |
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39,
|
| 65 |
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|
| 66 |
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41,
|
| 67 |
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42,
|
| 68 |
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43,
|
| 69 |
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44,
|
| 70 |
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45,
|
| 71 |
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46,
|
| 72 |
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47
|
| 73 |
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],
|
| 74 |
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"kinds": [
|
| 75 |
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"noul",
|
| 76 |
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"choice",
|
| 77 |
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"score"
|
| 78 |
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],
|
| 79 |
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"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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"model_version": "0.8.0",
|
| 81 |
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"lm_head_included": true,
|
| 82 |
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"weights_mode": "unmerged",
|
| 83 |
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"adapter_subfolder": "adapter",
|
| 84 |
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"lora": {
|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
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|
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|
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|
| 94 |
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|
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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},
|
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|
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|
| 103 |
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|
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|
| 105 |
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|
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|
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|
| 128 |
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|
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|
| 130 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 164 |
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|
e28/S1-E28-E18A050-rt-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
|
|
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|
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|
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|
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|
|
|
|
| 1 |
+
{"time": "06:07:41", "event": "start", "data": "data/e28/E28-E18A050-rt", "data_manifest": {"arm": "G-d512-n16k", "name": null, "train_sha256": "ef94315960694ce58bdc6d61b8665b7bf46f4e2996b9e82503e1d17bb87a14b7", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 4.799657821655273}
|
| 2 |
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{"time": "06:08:35", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 3335.8686490784153, "loss": 0.6002982165664434, "entropy": 0.5942575950175524, "sharp": 0.19537658989429474}
|
| 3 |
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{"time": "06:09:29", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 3347.89659647421, "loss": 0.6112224832177162, "entropy": 0.59024703130126, "sharp": 0.2019644845277071}
|
| 4 |
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{"time": "06:10:23", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 3353.529258976685, "loss": 0.6076782438904047, "entropy": 0.529285728931427, "sharp": 0.24768979381769896}
|
| 5 |
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{"time": "06:11:16", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 3359.1094743060803, "loss": 0.5808004774153233, "entropy": 0.6097748354077339, "sharp": 0.17353096511214972}
|
| 6 |
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{"time": "06:12:11", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 3369.3068844360805, "loss": 0.5585350655019283, "entropy": 0.5976961776614189, "sharp": 0.1846163496375084}
|
| 7 |
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{"time": "06:13:04", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 3375.8048401322844, "loss": 0.5941595509648323, "entropy": 0.6318124160170555, "sharp": 0.154153554700315}
|
| 8 |
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{"time": "06:13:58", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 3375.8535966310665, "loss": 0.5850520320236683, "entropy": 0.5771617069840431, "sharp": 0.20421438571065664}
|
| 9 |
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{"time": "06:14:52", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 3377.0916069751543, "loss": 0.6283475775271654, "entropy": 0.601615758612752, "sharp": 0.18012536317110062}
|
| 10 |
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{"time": "06:15:47", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 3380.7041022056424, "loss": 0.6425563246011734, "entropy": 0.594768863171339, "sharp": 0.17997646797448397}
|
| 11 |
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|
| 12 |
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|
| 13 |
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{"time": "06:17:54", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 3274.935834648614, "loss": 0.6264102570712566, "entropy": 0.6102959588170052, "sharp": 0.16732802893966436}
|
| 14 |
+
{"time": "06:18:50", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 3287.0189864821386, "loss": 0.5803467445075512, "entropy": 0.5993821527808905, "sharp": 0.17582901380956173}
|
| 15 |
+
{"time": "06:19:47", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 3297.0851454234808, "loss": 0.5702192187309265, "entropy": 0.5612410046160221, "sharp": 0.21354103833436966}
|
| 16 |
+
{"time": "06:20:41", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 3302.716488321634, "loss": 0.6200642455369234, "entropy": 0.6473408713936806, "sharp": 0.12580503337085247}
|
| 17 |
+
{"time": "06:21:36", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 3308.2881403457145, "loss": 0.6428153924643993, "entropy": 0.6326981969177723, "sharp": 0.14672968070954084}
|
| 18 |
+
{"time": "06:22:28", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 3312.8328430870833, "loss": 0.6297238897532225, "entropy": 0.5767229981720448, "sharp": 0.19916999712586403}
|
| 19 |
+
{"time": "06:23:23", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 3318.1738265316453, "loss": 0.6130420938134193, "entropy": 0.6221097409725189, "sharp": 0.15260346792638302}
|
| 20 |
+
{"time": "06:24:17", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 3322.7193927372523, "loss": 0.5934165082871914, "entropy": 0.6152561269700527, "sharp": 0.16756878979504108}
|
| 21 |
+
{"time": "06:25:11", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 3324.589217224558, "loss": 0.6296769827604294, "entropy": 0.6074256487190723, "sharp": 0.16790608409792185}
|
| 22 |
+
{"time": "06:26:05", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 3328.6099107837185, "loss": 0.5907804258167744, "entropy": 0.6081702299416065, "sharp": 0.18031224142760038}
|
| 23 |
+
{"time": "06:26:25", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.5784547328948975, "noul_T": 0.8328414215411776, "noul_auc": 0.7448313108639516, "noul_acc": 0.704, "noul_f1": 0.7620578778135049, "noul_nll": 0.5811050497889518, "noul_ece": 0.06479078799486161, "noul_brier": 0.19810341077413438, "noul_sharp": 0.17559659481048584, "entropy": 0.6053183078765869}
|
| 24 |
+
{"time": "06:27:20", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 3274.7058554089595, "loss": 0.586168397217989, "entropy": 0.5733136478811502, "sharp": 0.20715579017996788}
|
| 25 |
+
{"time": "06:28:13", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 3278.7195425829236, "loss": 0.6014519557356834, "entropy": 0.593541793525219, "sharp": 0.18261277489364147}
|
| 26 |
+
{"time": "06:29:06", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 3282.2559446384985, "loss": 0.5910805948078632, "entropy": 0.5957015547901392, "sharp": 0.19531946256756783}
|
| 27 |
+
{"time": "06:29:59", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 3285.9311897875646, "loss": 0.5925949309021235, "entropy": 0.5877530910074711, "sharp": 0.19521856494247913}
|
| 28 |
+
{"time": "06:30:57", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 3288.701294556637, "loss": 0.6153495758771896, "entropy": 0.6061336323618889, "sharp": 0.1711768750101328}
|
| 29 |
+
{"time": "06:31:48", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 3291.160656994244, "loss": 0.5898217596113682, "entropy": 0.6045204438269138, "sharp": 0.16672593727707863}
|
| 30 |
+
{"time": "06:32:41", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 3294.217945249048, "loss": 0.6414357991889119, "entropy": 0.6187189966440201, "sharp": 0.15950102172791958}
|
| 31 |
+
{"time": "06:33:34", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 3298.173177428458, "loss": 0.6342934807762504, "entropy": 0.6112399101257324, "sharp": 0.17046577669680119}
|
| 32 |
+
{"time": "06:34:29", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 3301.4133787114624, "loss": 0.617023091763258, "entropy": 0.5880597829818726, "sharp": 0.18076064437627792}
|
| 33 |
+
{"time": "06:35:24", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 3304.863377969232, "loss": 0.5869416482746601, "entropy": 0.5788372401148081, "sharp": 0.1744002364575863}
|
| 34 |
+
{"time": "06:35:44", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5695884227752686, "noul_T": 0.8970043922903317, "noul_auc": 0.7486624698317328, "noul_acc": 0.706, "noul_f1": 0.7692307692307693, "noul_nll": 0.5728995004072786, "noul_ece": 0.03249754613637924, "noul_brier": 0.19544740658234394, "noul_sharp": 0.18595445156097412, "entropy": 0.586853563785553}
|
| 35 |
+
{"time": "06:36:36", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 3268.4624207100774, "loss": 0.5773440040647984, "entropy": 0.6028434857726097, "sharp": 0.16967926733195782}
|
| 36 |
+
{"time": "06:37:27", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 3271.3165014306455, "loss": 0.6374371545389295, "entropy": 0.6155262598767877, "sharp": 0.16538868471980095}
|
| 37 |
+
{"time": "06:38:21", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 3275.03692884936, "loss": 0.5824361257255077, "entropy": 0.5844896733760834, "sharp": 0.18815483525395393}
|
| 38 |
+
{"time": "06:39:15", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 3278.093736059273, "loss": 0.6290938165038824, "entropy": 0.6002766862511635, "sharp": 0.17840714938938618}
|
| 39 |
+
{"time": "06:40:06", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 3281.1930558265444, "loss": 0.6121017262339592, "entropy": 0.61546690762043, "sharp": 0.14994669798761606}
|
| 40 |
+
{"time": "06:40:59", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 3284.7178698010935, "loss": 0.6235643997788429, "entropy": 0.598175898194313, "sharp": 0.18592064268887043}
|
| 41 |
+
{"time": "06:41:52", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 3288.22198246336, "loss": 0.6016076346859336, "entropy": 0.5771215986460447, "sharp": 0.20257375203073025}
|
| 42 |
+
{"time": "06:42:47", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 3290.5559815850797, "loss": 0.6171148121356964, "entropy": 0.6074099205434322, "sharp": 0.1688613723963499}
|
| 43 |
+
{"time": "06:43:43", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 3294.047448880535, "loss": 0.6298759374767542, "entropy": 0.6090978160500526, "sharp": 0.16564554441720247}
|
| 44 |
+
{"time": "06:44:35", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 3295.362348553038, "loss": 0.6032796315848827, "entropy": 0.607449185103178, "sharp": 0.16136501543223858}
|
| 45 |
+
{"time": "06:44:55", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5710271000862122, "noul_T": 0.8856563235718324, "noul_auc": 0.7491350356955999, "noul_acc": 0.712, "noul_f1": 0.7770897832817337, "noul_nll": 0.5730964285135269, "noul_ece": 0.03887997013330461, "noul_brier": 0.19541467243427132, "noul_sharp": 0.18427079916000366, "entropy": 0.590028703212738}
|
| 46 |
+
{"time": "06:45:48", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 3268.2654171836684, "loss": 0.6083678230643272, "entropy": 0.602668821811676, "sharp": 0.17243992909789085}
|
| 47 |
+
{"time": "06:46:40", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 3269.8583601611954, "loss": 0.6399169377982616, "entropy": 0.6169490301981568, "sharp": 0.15903472062200308}
|
| 48 |
+
{"time": "06:47:35", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 3272.142937401324, "loss": 0.612063997425139, "entropy": 0.5993046313524246, "sharp": 0.17189513705670834}
|
| 49 |
+
{"time": "06:48:27", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 3274.5345470432685, "loss": 0.6128622889518738, "entropy": 0.6048808097839355, "sharp": 0.16242566797882318}
|
| 50 |
+
{"time": "06:49:23", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 3276.7428045035026, "loss": 0.5755896419286728, "entropy": 0.6024290472269058, "sharp": 0.1778944954276085}
|
| 51 |
+
{"time": "06:50:14", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 3278.459756061006, "loss": 0.5963110364973545, "entropy": 0.5952213108539581, "sharp": 0.18893328122794628}
|
| 52 |
+
{"time": "06:51:06", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 3280.259019363613, "loss": 0.6257474981248379, "entropy": 0.6058809459209442, "sharp": 0.18065770715475082}
|
| 53 |
+
{"time": "06:52:02", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 3282.658107966944, "loss": 0.6027997732162476, "entropy": 0.5877076126635075, "sharp": 0.1966692004352808}
|
| 54 |
+
{"time": "06:52:58", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 3284.523572077551, "loss": 0.5845214314758778, "entropy": 0.5873317420482635, "sharp": 0.1952001266181469}
|
| 55 |
+
{"time": "06:53:53", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 3286.6416338650647, "loss": 0.5627817288041115, "entropy": 0.5550961457192898, "sharp": 0.23409852385520935}
|
| 56 |
+
{"time": "06:54:13", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5731131434440613, "noul_T": 0.8532130995982341, "noul_auc": 0.7512615820830029, "noul_acc": 0.704, "noul_f1": 0.765079365079365, "noul_nll": 0.5736514215767383, "noul_ece": 0.052701245307922376, "noul_brier": 0.1954938496230899, "noul_sharp": 0.17823639512062073, "entropy": 0.5969312787055969}
|
| 57 |
+
{"time": "06:54:56", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9113372, "tok_per_s": 3214.371023602123, "rows_per_s": 5.940329960631729, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5595800280570984, "noul_T": 0.8495371650607102, "choice_ce": 0.6842275261878967, "choice_T": 1.0560892190772713, "score_ce": 1.068756341934204, "score_T": 0.960112119036335, "noul_auc": 0.7447338666666667, "noul_acc": 0.695, "noul_f1": 0.7677075399847677, "noul_nll": 0.5717920997068286, "noul_ece": 0.04427964748442174, "noul_brier": 0.19495265463736913, "noul_sharp": 0.1802748143672943, "entropy": 0.5956453680992126}, "dropped_long": 0, "peak_gib": 18.284047603607178}
|
e28/S1-E28-E18A100-rt-syn/DONE
ADDED
|
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| 1 |
+
2026-10-21 05:41:56
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/README.md
ADDED
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|
| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- 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. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
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).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
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|
|
|
|
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|
|
|
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|
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|
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|
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|
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|
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|
| 7 |
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|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
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"bias": "none",
|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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"exclude_modules": null,
|
| 15 |
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"fan_in_fan_out": false,
|
| 16 |
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"inference_mode": true,
|
| 17 |
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"init_lora_weights": true,
|
| 18 |
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"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
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"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"v_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"k_proj",
|
| 42 |
+
"in_proj_qkv",
|
| 43 |
+
"in_proj_z",
|
| 44 |
+
"gate_proj",
|
| 45 |
+
"o_proj",
|
| 46 |
+
"up_proj",
|
| 47 |
+
"down_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
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"task_type": null,
|
| 51 |
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"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
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"use_dora": false,
|
| 54 |
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"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:bfe4f81b3bbc62200aedfb4e41c5a27c4008f64325bd8f3696c58e61dea1d9a4
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| 3 |
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size 160486456
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
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|
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| 37 |
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"target_modules": [
|
| 38 |
+
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|
| 39 |
+
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|
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+
"in_proj_qkv",
|
| 41 |
+
"in_proj_z",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"lm_head",
|
| 44 |
+
"o_proj",
|
| 45 |
+
"out_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
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"up_proj",
|
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"v_proj"
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],
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|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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e28/S1-E28-E18A100-rt-syn/ckpt-16000/adapter_vllm/decision_head.json
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| 9 |
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0.0012821187265217304,
|
| 10 |
+
-0.002416141564026475,
|
| 11 |
+
-0.00029356408049352467,
|
| 12 |
+
-0.0006167300161905587,
|
| 13 |
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-0.00018578222079668194,
|
| 14 |
+
0.0005398895591497421,
|
| 15 |
+
0.00042200679308734834,
|
| 16 |
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|
| 17 |
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| 18 |
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-0.00518615311011672,
|
| 19 |
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|
| 20 |
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-0.004403236787766218,
|
| 21 |
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-0.00495922239497304,
|
| 22 |
+
-0.005086651537567377,
|
| 23 |
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-0.003894349792972207,
|
| 24 |
+
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|
| 25 |
+
-0.005726017523556948,
|
| 26 |
+
-0.0035390020348131657
|
| 27 |
+
],
|
| 28 |
+
"verbalizer_ids": [
|
| 29 |
+
3721,
|
| 30 |
+
1802,
|
| 31 |
+
15,
|
| 32 |
+
16,
|
| 33 |
+
17,
|
| 34 |
+
18,
|
| 35 |
+
19,
|
| 36 |
+
20,
|
| 37 |
+
32,
|
| 38 |
+
33,
|
| 39 |
+
34,
|
| 40 |
+
35,
|
| 41 |
+
36,
|
| 42 |
+
37,
|
| 43 |
+
38,
|
| 44 |
+
39,
|
| 45 |
+
40,
|
| 46 |
+
41,
|
| 47 |
+
42,
|
| 48 |
+
43,
|
| 49 |
+
44,
|
| 50 |
+
45,
|
| 51 |
+
46,
|
| 52 |
+
47
|
| 53 |
+
],
|
| 54 |
+
"slots": {
|
| 55 |
+
"num_slots": 24,
|
| 56 |
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"ranges": {
|
| 57 |
+
"noul": [
|
| 58 |
+
0,
|
| 59 |
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2
|
| 60 |
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],
|
| 61 |
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"score": [
|
| 62 |
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2,
|
| 63 |
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8
|
| 64 |
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],
|
| 65 |
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"choice": [
|
| 66 |
+
8,
|
| 67 |
+
24
|
| 68 |
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]
|
| 69 |
+
},
|
| 70 |
+
"verbalizers": [
|
| 71 |
+
"false",
|
| 72 |
+
"true",
|
| 73 |
+
"0",
|
| 74 |
+
"1",
|
| 75 |
+
"2",
|
| 76 |
+
"3",
|
| 77 |
+
"4",
|
| 78 |
+
"5",
|
| 79 |
+
"A",
|
| 80 |
+
"B",
|
| 81 |
+
"C",
|
| 82 |
+
"D",
|
| 83 |
+
"E",
|
| 84 |
+
"F",
|
| 85 |
+
"G",
|
| 86 |
+
"H",
|
| 87 |
+
"I",
|
| 88 |
+
"J",
|
| 89 |
+
"K",
|
| 90 |
+
"L",
|
| 91 |
+
"M",
|
| 92 |
+
"N",
|
| 93 |
+
"O",
|
| 94 |
+
"P"
|
| 95 |
+
],
|
| 96 |
+
"template_version": "bare-v1"
|
| 97 |
+
},
|
| 98 |
+
"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"version": 1,
|
| 3 |
+
"per_kind": {
|
| 4 |
+
"noul": 0.8950098446145761,
|
| 5 |
+
"choice": 0.979539418518294,
|
| 6 |
+
"score": 0.9799331682889751
|
| 7 |
+
},
|
| 8 |
+
"fit": {
|
| 9 |
+
"noul": {
|
| 10 |
+
"n": 1087,
|
| 11 |
+
"T": 0.8950098446145761,
|
| 12 |
+
"ce_before": 0.5527104139328003,
|
| 13 |
+
"ce_after": 0.5517128109931946
|
| 14 |
+
},
|
| 15 |
+
"choice": {
|
| 16 |
+
"n": 60,
|
| 17 |
+
"T": 0.979539418518294,
|
| 18 |
+
"ce_before": 0.6627646684646606,
|
| 19 |
+
"ce_after": 0.6626709699630737
|
| 20 |
+
},
|
| 21 |
+
"score": {
|
| 22 |
+
"n": 53,
|
| 23 |
+
"T": 0.9799331682889751,
|
| 24 |
+
"ce_before": 1.0634764432907104,
|
| 25 |
+
"ce_after": 1.0633518695831299
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"source": "models/e28/S1-E28-E18A100-rt-syn/ckpt-16000"
|
| 29 |
+
}
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:d934b88b444bb3cdf13f80e6ae05713ce4742c3c68bf0753ad84e6bbef715ffa
|
| 3 |
+
size 393464
|
e28/S1-E28-E18A100-rt-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"base_model_path": "/root/models/Qwen3.5-9B",
|
| 3 |
+
"hidden_size": 4096,
|
| 4 |
+
"slots": {
|
| 5 |
+
"num_slots": 24,
|
| 6 |
+
"ranges": {
|
| 7 |
+
"noul": [
|
| 8 |
+
0,
|
| 9 |
+
2
|
| 10 |
+
],
|
| 11 |
+
"score": [
|
| 12 |
+
2,
|
| 13 |
+
8
|
| 14 |
+
],
|
| 15 |
+
"choice": [
|
| 16 |
+
8,
|
| 17 |
+
24
|
| 18 |
+
]
|
| 19 |
+
},
|
| 20 |
+
"verbalizers": [
|
| 21 |
+
"false",
|
| 22 |
+
"true",
|
| 23 |
+
"0",
|
| 24 |
+
"1",
|
| 25 |
+
"2",
|
| 26 |
+
"3",
|
| 27 |
+
"4",
|
| 28 |
+
"5",
|
| 29 |
+
"A",
|
| 30 |
+
"B",
|
| 31 |
+
"C",
|
| 32 |
+
"D",
|
| 33 |
+
"E",
|
| 34 |
+
"F",
|
| 35 |
+
"G",
|
| 36 |
+
"H",
|
| 37 |
+
"I",
|
| 38 |
+
"J",
|
| 39 |
+
"K",
|
| 40 |
+
"L",
|
| 41 |
+
"M",
|
| 42 |
+
"N",
|
| 43 |
+
"O",
|
| 44 |
+
"P"
|
| 45 |
+
],
|
| 46 |
+
"template_version": "bare-v1"
|
| 47 |
+
},
|
| 48 |
+
"verbalizer_ids": [
|
| 49 |
+
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|
| 50 |
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|
| 51 |
+
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|
| 52 |
+
16,
|
| 53 |
+
17,
|
| 54 |
+
18,
|
| 55 |
+
19,
|
| 56 |
+
20,
|
| 57 |
+
32,
|
| 58 |
+
33,
|
| 59 |
+
34,
|
| 60 |
+
35,
|
| 61 |
+
36,
|
| 62 |
+
37,
|
| 63 |
+
38,
|
| 64 |
+
39,
|
| 65 |
+
40,
|
| 66 |
+
41,
|
| 67 |
+
42,
|
| 68 |
+
43,
|
| 69 |
+
44,
|
| 70 |
+
45,
|
| 71 |
+
46,
|
| 72 |
+
47
|
| 73 |
+
],
|
| 74 |
+
"kinds": [
|
| 75 |
+
"noul",
|
| 76 |
+
"choice",
|
| 77 |
+
"score"
|
| 78 |
+
],
|
| 79 |
+
"model_name": "jev-judge-qwen35-9b",
|
| 80 |
+
"model_version": "0.8.0",
|
| 81 |
+
"lm_head_included": true,
|
| 82 |
+
"weights_mode": "unmerged",
|
| 83 |
+
"adapter_subfolder": "adapter",
|
| 84 |
+
"lora": {
|
| 85 |
+
"r": 16,
|
| 86 |
+
"lora_alpha": 32,
|
| 87 |
+
"lora_dropout": 0.05,
|
| 88 |
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"target_modules": [
|
| 89 |
+
"down_proj",
|
| 90 |
+
"gate_proj",
|
| 91 |
+
"in_proj_qkv",
|
| 92 |
+
"in_proj_z",
|
| 93 |
+
"k_proj",
|
| 94 |
+
"o_proj",
|
| 95 |
+
"out_proj",
|
| 96 |
+
"q_proj",
|
| 97 |
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"up_proj",
|
| 98 |
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"v_proj"
|
| 99 |
+
]
|
| 100 |
+
},
|
| 101 |
+
"trained_stage": "e16",
|
| 102 |
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"source_checkpoint": "models/e28/S1-E28-E18A100-rt-syn/ckpt-16000",
|
| 103 |
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"softcap": null,
|
| 104 |
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"e16": {
|
| 105 |
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"data": "data/e28/E28-E18A100-rt",
|
| 106 |
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"data_manifest": {
|
| 107 |
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"arm": "G-d512-n16k-a100",
|
| 108 |
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"name": null,
|
| 109 |
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| 110 |
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"n_train": 16000
|
| 111 |
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},
|
| 112 |
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"init": "released",
|
| 113 |
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"objective": "s-log",
|
| 114 |
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"sigma": 0.5,
|
| 115 |
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"K": 8,
|
| 116 |
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"reward": "brier",
|
| 117 |
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"clip": 0.2,
|
| 118 |
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"passes": 1,
|
| 119 |
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"lr": 0.0001,
|
| 120 |
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"lr_head": 0.0002,
|
| 121 |
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"rows_per_step": 32,
|
| 122 |
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"train_seed": 0,
|
| 123 |
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"replay": "data/e16/replay/train.jsonl",
|
| 124 |
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"replay_frac": 0.05,
|
| 125 |
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"replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e",
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| 126 |
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"max_len": 3072,
|
| 127 |
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"schedule": "warmup 0.03 + cosine to x0.05 over 500 steps",
|
| 128 |
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"total_rows": 16000,
|
| 129 |
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"lora": {
|
| 130 |
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"r": 16,
|
| 131 |
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"lora_alpha": 32,
|
| 132 |
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"lora_dropout": 0.05
|
| 133 |
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},
|
| 134 |
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"trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3",
|
| 135 |
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"event": "ckpt",
|
| 136 |
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"tag": "ckpt-16000",
|
| 137 |
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"rows_seen": 16000,
|
| 138 |
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"replay_seen": 842,
|
| 139 |
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"step": 500,
|
| 140 |
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"tokens": 9113372,
|
| 141 |
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"tok_per_s": 3211.5324866181877,
|
| 142 |
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"rows_per_s": 5.935084194122323,
|
| 143 |
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"val": {
|
| 144 |
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"n": 1200,
|
| 145 |
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"dropped_long": 0,
|
| 146 |
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"noul_ce": 0.5527104139328003,
|
| 147 |
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"noul_T": 0.8950098446145761,
|
| 148 |
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"choice_ce": 0.6627646684646606,
|
| 149 |
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"choice_T": 0.979539418518294,
|
| 150 |
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"score_ce": 1.0634764432907104,
|
| 151 |
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"score_T": 0.9799331682889751,
|
| 152 |
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"noul_auc": 0.7475370666666667,
|
| 153 |
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"noul_acc": 0.709,
|
| 154 |
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"noul_f1": 0.7826736370425691,
|
| 155 |
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"noul_nll": 0.5664274678044021,
|
| 156 |
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"noul_ece": 0.02627825298905373,
|
| 157 |
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"noul_brier": 0.19344517944405668,
|
| 158 |
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"noul_sharp": 0.18980935215950012,
|
| 159 |
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"entropy": 0.5791373252868652
|
| 160 |
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},
|
| 161 |
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"dropped_long": 0,
|
| 162 |
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"peak_gib": 18.284047603607178
|
| 163 |
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}
|
| 164 |
+
}
|
e28/S1-E28-E18A100-rt-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- 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. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
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).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"v_proj",
|
| 40 |
+
"gate_proj",
|
| 41 |
+
"in_proj_z",
|
| 42 |
+
"up_proj",
|
| 43 |
+
"o_proj",
|
| 44 |
+
"q_proj",
|
| 45 |
+
"k_proj",
|
| 46 |
+
"down_proj",
|
| 47 |
+
"in_proj_qkv"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
+
"task_type": null,
|
| 51 |
+
"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
+
"use_dora": false,
|
| 54 |
+
"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d78eef6a2ecf5d7a7fa2e3e767d90b6a47985a8b9f58e1394629c81783d1bcc5
|
| 3 |
+
size 160486456
|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": null,
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 64.0,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.0,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
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"peft_type": "LORA",
|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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"target_modules": [
|
| 38 |
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"down_proj",
|
| 39 |
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|
| 40 |
+
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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| 49 |
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],
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| 50 |
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|
| 51 |
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|
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|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 176641832
|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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| 87 |
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| 89 |
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| 95 |
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| 96 |
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| 97 |
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| 98 |
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|
| 99 |
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|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
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{
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|
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| 28 |
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"source": "models/e28/S1-E28-E30-a1-rw-syn/ckpt-16000"
|
| 29 |
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|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 3 |
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size 393464
|
e28/S1-E28-E30-a1-rw-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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| 1 |
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{
|
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|
| 3 |
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|
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| 21 |
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| 22 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 44 |
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| 45 |
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| 46 |
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| 47 |
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| 76 |
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| 82 |
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| 163 |
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|
| 164 |
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|
e28/S1-E28-E30-a1-rw-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
+
{"time": "17:54:43", "event": "start", "data": "data/e28/E28-E30-a1-rw", "data_manifest": {"arm": "E28-E30-a1-rw", "name": null, "train_sha256": "d26b35d46e3927d8807524aa9b0efcfcb8505a3ac3b2c30a9a2933198ec3e62d", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 4.869741678237915}
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| 51 |
+
{"time": "18:35:58", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 3342.722650089894, "loss": 0.6680366033688188, "entropy": 0.6582284085452557, "sharp": 0.10449005477130413}
|
| 52 |
+
{"time": "18:36:50", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 3344.5248878335597, "loss": 0.6666250005364418, "entropy": 0.6220298185944557, "sharp": 0.15243109688162804}
|
| 53 |
+
{"time": "18:37:42", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 3346.176169703262, "loss": 0.6240421757102013, "entropy": 0.6295576170086861, "sharp": 0.13606482464820147}
|
| 54 |
+
{"time": "18:38:33", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 3349.000266115592, "loss": 0.6278671249747276, "entropy": 0.6624680310487747, "sharp": 0.09166452661156654}
|
| 55 |
+
{"time": "18:39:25", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 3351.4645199172123, "loss": 0.7027888223528862, "entropy": 0.6221847385168076, "sharp": 0.15409976709634066}
|
| 56 |
+
{"time": "18:39:45", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.6007530093193054, "noul_T": 0.7747629570244622, "noul_auc": 0.7332196924946415, "noul_acc": 0.708, "noul_f1": 0.7660256410256411, "noul_nll": 0.5951983838230371, "noul_ece": 0.08512620198726653, "noul_brier": 0.20347204683407666, "noul_sharp": 0.14822502434253693, "entropy": 0.6300143599510193}
|
| 57 |
+
{"time": "18:40:28", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 8988859, "tok_per_s": 3275.2473404806465, "rows_per_s": 6.13667604304651, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5852800011634827, "noul_T": 0.7893042861110305, "choice_ce": 0.6824166774749756, "choice_T": 1.1089171735549759, "score_ce": 1.0658724308013916, "score_T": 0.9725362941237807, "noul_auc": 0.7184704, "noul_acc": 0.696, "noul_f1": 0.76793893129771, "noul_nll": 0.5946063060313463, "noul_ece": 0.059608851045370115, "noul_brier": 0.20349168514643015, "noul_sharp": 0.15316306054592133, "entropy": 0.6263568997383118}, "dropped_long": 0, "peak_gib": 18.282336711883545}
|
e28/S1-E28-E30-a1-uni-syn/DONE
ADDED
|
@@ -0,0 +1 @@
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| 1 |
+
2026-10-21 17:27:13
|
e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/README.md
ADDED
|
@@ -0,0 +1,206 @@
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| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- 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. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
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).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
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|
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|
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|
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|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
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"r": 16,
|
| 35 |
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"rank_pattern": {},
|
| 36 |
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"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
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"in_proj_z",
|
| 40 |
+
"k_proj",
|
| 41 |
+
"o_proj",
|
| 42 |
+
"v_proj",
|
| 43 |
+
"gate_proj",
|
| 44 |
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"in_proj_qkv",
|
| 45 |
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"down_proj",
|
| 46 |
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"q_proj",
|
| 47 |
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"up_proj"
|
| 48 |
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],
|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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}
|
e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0bc376b8094b519732e128bc6c2e77088496bc2b7ef13135e140ee0912c34be
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| 3 |
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size 160486456
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e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
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|
|
|
|
|
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|
|
|
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|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
|
|
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|
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|
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|
|
|
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|
|
|
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|
|
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|
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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"alpha_pattern": {},
|
| 4 |
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|
| 5 |
+
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|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
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|
| 10 |
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"bias": "none",
|
| 11 |
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|
| 12 |
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"ensure_weight_tying": false,
|
| 13 |
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"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
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"fan_in_fan_out": false,
|
| 16 |
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"inference_mode": true,
|
| 17 |
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"init_lora_weights": true,
|
| 18 |
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"kasa_config": null,
|
| 19 |
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"layer_replication": null,
|
| 20 |
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"layers_pattern": null,
|
| 21 |
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"layers_to_transform": null,
|
| 22 |
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"loftq_config": {},
|
| 23 |
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"lora_alpha": 64.0,
|
| 24 |
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"lora_bias": false,
|
| 25 |
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"lora_dropout": 0.0,
|
| 26 |
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"lora_ga_config": null,
|
| 27 |
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"megatron_config": null,
|
| 28 |
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"megatron_core": "megatron.core",
|
| 29 |
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"modules_to_save": null,
|
| 30 |
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"monteclora_config": null,
|
| 31 |
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"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
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"qalora_group_size": 16,
|
| 34 |
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"r": 32,
|
| 35 |
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"rank_pattern": {},
|
| 36 |
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"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"down_proj",
|
| 39 |
+
"gate_proj",
|
| 40 |
+
"in_proj_qkv",
|
| 41 |
+
"in_proj_z",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"lm_head",
|
| 44 |
+
"o_proj",
|
| 45 |
+
"out_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
+
"up_proj",
|
| 48 |
+
"v_proj"
|
| 49 |
+
],
|
| 50 |
+
"target_parameters": null,
|
| 51 |
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"task_type": null,
|
| 52 |
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"trainable_token_indices": null,
|
| 53 |
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"use_bdlora": null,
|
| 54 |
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"use_dora": false,
|
| 55 |
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"use_qalora": false,
|
| 56 |
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"use_rslora": false,
|
| 57 |
+
"velora_config": null
|
| 58 |
+
}
|
e28/S1-E28-E30-a1-uni-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cd954b72350ecb7f709fe16b769604f928bdb583b488ca6aa79d7f8adf78ca5b
|
| 3 |
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size 176641832
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