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
backup e15/F1-LODO-dbe_kt22 (Pod B)
Browse files- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/README.md +206 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/adapter_config.json +57 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/adapter_model.safetensors +3 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/adapter_config.json +58 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/adapter_model.safetensors +3 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/decision_head.json +99 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/calibration.json +17 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/head.safetensors +3 -0
- e15/F1-LODO-dbe_kt22/ckpt-4000/judge_config.json +145 -0
- e15/F1-LODO-dbe_kt22/train_log.jsonl +15 -0
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/README.md
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| 1 |
+
---
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| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
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| 3 |
+
library_name: peft
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| 4 |
+
tags:
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| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
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| 6 |
+
- lora
|
| 7 |
+
- transformers
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| 8 |
+
---
|
| 9 |
+
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| 10 |
+
# Model Card for Model ID
|
| 11 |
+
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| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
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| 14 |
+
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| 15 |
+
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| 16 |
+
## Model Details
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| 17 |
+
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| 18 |
+
### Model Description
|
| 19 |
+
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| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
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| 22 |
+
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| 23 |
+
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| 24 |
+
- **Developed by:** [More Information Needed]
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| 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 |
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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 |
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|
| 92 |
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#### Preprocessing [optional]
|
| 93 |
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|
| 94 |
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[More Information Needed]
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| 95 |
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|
| 96 |
+
|
| 97 |
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#### Training Hyperparameters
|
| 98 |
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|
| 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 |
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|
| 103 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
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|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
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| 110 |
+
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| 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 |
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| 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 |
+
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| 165 |
+
[More Information Needed]
|
| 166 |
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|
| 167 |
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#### Hardware
|
| 168 |
+
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| 169 |
+
[More Information Needed]
|
| 170 |
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|
| 171 |
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#### Software
|
| 172 |
+
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| 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 |
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|
| 193 |
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## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
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## Model Card Authors [optional]
|
| 198 |
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| 199 |
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[More Information Needed]
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| 200 |
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|
| 201 |
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## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
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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 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"gate_proj",
|
| 40 |
+
"down_proj",
|
| 41 |
+
"in_proj_qkv",
|
| 42 |
+
"o_proj",
|
| 43 |
+
"q_proj",
|
| 44 |
+
"in_proj_z",
|
| 45 |
+
"v_proj",
|
| 46 |
+
"up_proj",
|
| 47 |
+
"k_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 |
+
}
|
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter/adapter_model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fbc8e3b2832934ef04748614775ac176cfd8912559da25d5245bf0c4c79a14af
|
| 3 |
+
size 160486456
|
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/adapter_config.json
ADDED
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@@ -0,0 +1,58 @@
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|
| 7 |
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|
| 8 |
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| 13 |
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| 14 |
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| 15 |
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| 16 |
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|
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|
| 27 |
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|
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| 29 |
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|
| 30 |
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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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|
| 48 |
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|
| 49 |
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| 50 |
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|
| 51 |
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|
| 58 |
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|
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/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 sha256:9844fba43ad1a68d3e371b86e82fcacf6e72df225676f763aa943d253018357b
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| 3 |
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size 176641832
|
e15/F1-LODO-dbe_kt22/ckpt-4000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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| 60 |
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|
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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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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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| 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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|
| 91 |
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| 92 |
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| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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"template_version": "bare-v1"
|
| 97 |
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},
|
| 98 |
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"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
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|
e15/F1-LODO-dbe_kt22/ckpt-4000/calibration.json
ADDED
|
@@ -0,0 +1,17 @@
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| 1 |
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{
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|
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| 7 |
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},
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|
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|
| 14 |
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|
| 15 |
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},
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| 16 |
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"source": "models/e15/F1-LODO-dbe_kt22/ckpt-4000"
|
| 17 |
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}
|
e15/F1-LODO-dbe_kt22/ckpt-4000/head.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 sha256:45145f8bb80b9108b8751776da907492686219c4429edabf1bed2d48720032d3
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size 393464
|
e15/F1-LODO-dbe_kt22/ckpt-4000/judge_config.json
ADDED
|
@@ -0,0 +1,145 @@
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|
| 1 |
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| 2 |
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|
| 3 |
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|
| 4 |
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| 11 |
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| 17 |
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| 18 |
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| 19 |
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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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|
| 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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| 48 |
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| 50 |
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| 58 |
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| 59 |
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| 60 |
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| 63 |
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| 64 |
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| 66 |
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| 69 |
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| 70 |
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| 71 |
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|
| 72 |
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| 73 |
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| 74 |
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"kinds": [
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| 75 |
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|
| 76 |
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|
| 77 |
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|
| 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": {
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| 85 |
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|
| 86 |
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"lora_alpha": 32,
|
| 87 |
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|
| 88 |
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"target_modules": [
|
| 89 |
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|
| 90 |
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|
| 91 |
+
"in_proj_qkv",
|
| 92 |
+
"in_proj_z",
|
| 93 |
+
"k_proj",
|
| 94 |
+
"o_proj",
|
| 95 |
+
"out_proj",
|
| 96 |
+
"q_proj",
|
| 97 |
+
"up_proj",
|
| 98 |
+
"v_proj"
|
| 99 |
+
]
|
| 100 |
+
},
|
| 101 |
+
"trained_stage": "e15",
|
| 102 |
+
"source_checkpoint": "models/e15/F1-LODO-dbe_kt22/ckpt-4000",
|
| 103 |
+
"softcap": null,
|
| 104 |
+
"e15": {
|
| 105 |
+
"data": "data/e15/F1-LODO-dbe_kt22",
|
| 106 |
+
"data_manifest": {
|
| 107 |
+
"arm": "F1-LODO",
|
| 108 |
+
"name": "F1-LODO-dbe_kt22",
|
| 109 |
+
"train_sha256": "4ac935f5a6260cdaa14f74ba3ba09b19b0a9151400f96add2c9357278315e407",
|
| 110 |
+
"n_train": 16000
|
| 111 |
+
},
|
| 112 |
+
"init": "released",
|
| 113 |
+
"lr": 0.0001,
|
| 114 |
+
"lr_head": 0.0002,
|
| 115 |
+
"rows_per_step": 32,
|
| 116 |
+
"skip_rows": 0,
|
| 117 |
+
"epochs": 1,
|
| 118 |
+
"max_len": 3072,
|
| 119 |
+
"schedule": "warmup 0.03 + cosine to x0.05 over 125 steps",
|
| 120 |
+
"total_rows": 4000,
|
| 121 |
+
"lora": {
|
| 122 |
+
"r": 16,
|
| 123 |
+
"lora_alpha": 32,
|
| 124 |
+
"lora_dropout": 0.05
|
| 125 |
+
},
|
| 126 |
+
"event": "ckpt",
|
| 127 |
+
"tag": "ckpt-4000",
|
| 128 |
+
"rows_seen": 4000,
|
| 129 |
+
"step": 125,
|
| 130 |
+
"tokens": 2676235,
|
| 131 |
+
"tok_per_s": 788.7951158452983,
|
| 132 |
+
"val": {
|
| 133 |
+
"n": 2000,
|
| 134 |
+
"dropped_long": 0,
|
| 135 |
+
"noul_ce": 0.5250526666641235,
|
| 136 |
+
"kt_auc": 0.7884966488030971,
|
| 137 |
+
"kt_acc": 0.727,
|
| 138 |
+
"kt_f1": 0.7988209285187915,
|
| 139 |
+
"kt_ece": 0.031544476196169846,
|
| 140 |
+
"kt_nll": 0.5250526433140039
|
| 141 |
+
},
|
| 142 |
+
"dropped_long": 0,
|
| 143 |
+
"peak_gib": 18.235835075378418
|
| 144 |
+
}
|
| 145 |
+
}
|
e15/F1-LODO-dbe_kt22/train_log.jsonl
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time": "11:52:16", "event": "start", "model_dir": "/workspace/jev_kt/models/hf/JEV-9B", "init": "released", "device": "cuda", "load_s": 116.84268808364868, "trainable_lora": 40108032, "head": 98328}
|
| 2 |
+
{"time": "11:52:16", "event": "run", "data": "data/e15/F1-LODO-dbe_kt22", "out": "models/e15/F1-LODO-dbe_kt22"}
|
| 3 |
+
{"time": "11:56:15", "event": "step", "step": 10, "rows_seen": 320, "loss": 0.5597564838826656, "lr": 9.923040269974204e-05, "tok_per_s": 892.8252975586905}
|
| 4 |
+
{"time": "12:00:03", "event": "step", "step": 20, "rows_seen": 640, "loss": 0.5784428040497005, "lr": 9.55208574963224e-05, "tok_per_s": 894.8125098288366}
|
| 5 |
+
{"time": "12:04:01", "event": "step", "step": 30, "rows_seen": 960, "loss": 0.5129471104592085, "lr": 8.897432118673851e-05, "tok_per_s": 894.4637446827277}
|
| 6 |
+
{"time": "12:08:09", "event": "step", "step": 40, "rows_seen": 1280, "loss": 0.5547890234738588, "lr": 8.002250216471678e-05, "tok_per_s": 893.6722284018406}
|
| 7 |
+
{"time": "12:12:10", "event": "step", "step": 50, "rows_seen": 1600, "loss": 0.5228286869823933, "lr": 6.925572411108201e-05, "tok_per_s": 894.8327824116469}
|
| 8 |
+
{"time": "12:16:10", "event": "step", "step": 60, "rows_seen": 1920, "loss": 0.5534754495602101, "lr": 5.738399736402462e-05, "tok_per_s": 895.0990084125132}
|
| 9 |
+
{"time": "12:20:14", "event": "step", "step": 70, "rows_seen": 2240, "loss": 0.5427125189453363, "lr": 4.519019760655705e-05, "tok_per_s": 894.2532345253351}
|
| 10 |
+
{"time": "12:24:15", "event": "step", "step": 80, "rows_seen": 2560, "loss": 0.6720086908899248, "lr": 3.3478439481564835e-05, "tok_per_s": 894.7767451747436}
|
| 11 |
+
{"time": "12:28:15", "event": "step", "step": 90, "rows_seen": 2880, "loss": 0.6765209548175335, "lr": 2.3021049613197416e-05, "tok_per_s": 895.3720997476648}
|
| 12 |
+
{"time": "12:32:19", "event": "step", "step": 100, "rows_seen": 3200, "loss": 0.5380632318556309, "lr": 1.4507635874863332e-05, "tok_per_s": 894.9713351437393}
|
| 13 |
+
{"time": "12:36:08", "event": "step", "step": 110, "rows_seen": 3520, "loss": 0.43723529763519764, "lr": 8.49961150805399e-06, "tok_per_s": 894.3180238929058}
|
| 14 |
+
{"time": "12:40:05", "event": "step", "step": 120, "rows_seen": 3840, "loss": 0.41409095004200935, "lr": 5.3931729785351795e-06, "tok_per_s": 895.135348325423}
|
| 15 |
+
{"time": "12:48:51", "event": "ckpt", "tag": "ckpt-4000", "rows_seen": 4000, "step": 125, "tokens": 2676235, "tok_per_s": 788.7951158452983, "val": {"n": 2000, "dropped_long": 0, "noul_ce": 0.5250526666641235, "kt_auc": 0.7884966488030971, "kt_acc": 0.727, "kt_f1": 0.7988209285187915, "kt_ece": 0.031544476196169846, "kt_nll": 0.5250526433140039}, "dropped_long": 0, "peak_gib": 18.235835075378418}
|