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 e16/S1-E19-a1-n16k-a100-syn (Pod B)
Browse files- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/README.md +206 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/calibration.json +29 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/head.safetensors +3 -0
- e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/judge_config.json +164 -0
- e16/S1-E19-a1-n16k-a100-syn/train_log.jsonl +57 -0
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/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 |
+
---
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| 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 |
+
|
| 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
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| 19 |
+
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| 20 |
+
<!-- Provide a longer summary of what this model is. -->
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| 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 |
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|
| 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 |
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|
| 78 |
+
[More Information Needed]
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| 79 |
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|
| 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 |
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|
| 86 |
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[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 |
+
#### 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 |
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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 |
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[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 |
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| 121 |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
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|
| 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 |
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| 163 |
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### Compute Infrastructure
|
| 164 |
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| 165 |
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[More Information Needed]
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| 166 |
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|
| 167 |
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#### Hardware
|
| 168 |
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| 169 |
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[More Information Needed]
|
| 170 |
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|
| 171 |
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#### Software
|
| 172 |
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| 173 |
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[More Information Needed]
|
| 174 |
+
|
| 175 |
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## 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 |
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[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 |
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[More Information Needed]
|
| 192 |
+
|
| 193 |
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## More Information [optional]
|
| 194 |
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|
| 195 |
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[More Information Needed]
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| 196 |
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|
| 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 |
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[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
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| 1 |
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{
|
| 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 |
+
"up_proj",
|
| 39 |
+
"o_proj",
|
| 40 |
+
"out_proj",
|
| 41 |
+
"in_proj_qkv",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"v_proj",
|
| 44 |
+
"q_proj",
|
| 45 |
+
"gate_proj",
|
| 46 |
+
"in_proj_z",
|
| 47 |
+
"down_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 |
+
}
|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26bbff256f6baec9e9ec8da2de01f76d2f215be87699a7084263a8f28864d4eb
|
| 3 |
+
size 160486456
|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
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@@ -0,0 +1,58 @@
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|
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|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/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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| 3 |
+
size 176641832
|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/calibration.json
ADDED
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| 29 |
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|
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/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 sha256:27596691b6abf3b704e42390db2337e6cef8b3ebc55e727735729770c6de1342
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| 3 |
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size 393464
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e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
| 1 |
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{
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| 2 |
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| 3 |
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| 23 |
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| 25 |
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| 28 |
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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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| 49 |
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| 50 |
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|
e16/S1-E19-a1-n16k-a100-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
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{"time": "10:22:59", "event": "start", "data": "data/e19/E19-a1-n16k-a100", "data_manifest": {"arm": "E19-a1-n16k-a100", "name": null, "train_sha256": "e8630093337aa4e236ec84240be87518ce2f248884bb346f205966a4da98bbe6", "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": "bc7c08e836bd99bb2665b02903cd41404ea029ecfa9b68a9ec1a7cda96958ba4", "device": "cuda", "load_s": 82.36370635032654}
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{"time": "12:41:02", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 820.4543170265516, "loss": 0.6043067872524261, "entropy": 0.5097386874258518, "sharp": 0.25294330157339573}
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{"time": "12:49:25", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.6663276553153992, "noul_T": 1.5120448444779917, "noul_auc": 0.7131187659280013, "noul_acc": 0.618, "noul_f1": 0.6375711574952562, "noul_nll": 0.6587968682050704, "noul_ece": 0.1698397262990475, "noul_brier": 0.2323156793457572, "noul_sharp": 0.14484210312366486, "entropy": 0.6248260140419006}
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{"time": "12:52:55", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 814.5441762398887, "loss": 0.6182875856757164, "entropy": 0.5299367345869541, "sharp": 0.24415271915495396}
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{"time": "12:56:28", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 815.3198678596252, "loss": 0.7247134894132614, "entropy": 0.5087413843721151, "sharp": 0.2524926494807005}
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| 49 |
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| 50 |
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