Unggi commited on
Commit
e5fff96
·
verified ·
1 Parent(s): 55fcca0

backup e16/S1-E19-a1-n16k-a100-syn (Pod B)

Browse files
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter/README.md ADDED
@@ -0,0 +1,206 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
e16/S1-E19-a1-n16k-a100-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
+ "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
@@ -0,0 +1,3 @@
 
 
 
 
1
+ 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
@@ -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
+ "peft_type": "LORA",
32
+ "peft_version": "0.21.0",
33
+ "qalora_group_size": 16,
34
+ "r": 32,
35
+ "rank_pattern": {},
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
+ "target_parameters": null,
51
+ "task_type": null,
52
+ "trainable_token_indices": null,
53
+ "use_bdlora": null,
54
+ "use_dora": false,
55
+ "use_qalora": false,
56
+ "use_rslora": false,
57
+ "velora_config": null
58
+ }
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:15da5e9783bcf65909b1f5ff55cd13f00a14d021f4e874a9c9f3d9df33d9bc6f
3
+ size 176641832
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bias": [
3
+ 0.0008848350844345987,
4
+ -0.000885090499650687,
5
+ -0.002075083553791046,
6
+ -0.0014754201984032989,
7
+ -0.00027172418776899576,
8
+ 0.0017720174510031939,
9
+ 0.000912531919311732,
10
+ -0.00246368907392025,
11
+ -0.0011163590243086219,
12
+ -0.000942745478823781,
13
+ -0.0003056631830986589,
14
+ 0.0002605628105811775,
15
+ -0.0010928282281383872,
16
+ -0.003883223980665207,
17
+ -0.004518965259194374,
18
+ -0.005214374046772718,
19
+ -0.005939367692917585,
20
+ -0.004417700227349997,
21
+ -0.00497456407174468,
22
+ -0.005170551594346762,
23
+ -0.004228414501994848,
24
+ -0.0036207044031471014,
25
+ -0.005773615092039108,
26
+ -0.0036045874003320932
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
+ "ranges": {
57
+ "noul": [
58
+ 0,
59
+ 2
60
+ ],
61
+ "score": [
62
+ 2,
63
+ 8
64
+ ],
65
+ "choice": [
66
+ 8,
67
+ 24
68
+ ]
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
+ }
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/calibration.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "version": 1,
3
+ "per_kind": {
4
+ "noul": 1.029952342237469,
5
+ "choice": 1.0577606522158263,
6
+ "score": 0.9693892850617055
7
+ },
8
+ "fit": {
9
+ "noul": {
10
+ "n": 1087,
11
+ "T": 1.029952342237469,
12
+ "ce_before": 0.6381511092185974,
13
+ "ce_after": 0.6381175518035889
14
+ },
15
+ "choice": {
16
+ "n": 60,
17
+ "T": 1.0577606522158263,
18
+ "ce_before": 0.6812111735343933,
19
+ "ce_after": 0.6804530620574951
20
+ },
21
+ "score": {
22
+ "n": 53,
23
+ "T": 0.9693892850617055,
24
+ "ce_before": 1.0487253665924072,
25
+ "ce_after": 1.0484395027160645
26
+ }
27
+ },
28
+ "source": "models/e16/S1-E19-a1-n16k-a100-syn/ckpt-16000"
29
+ }
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/head.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:27596691b6abf3b704e42390db2337e6cef8b3ebc55e727735729770c6de1342
3
+ size 393464
e16/S1-E19-a1-n16k-a100-syn/ckpt-16000/judge_config.json ADDED
@@ -0,0 +1,164 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ 3721,
50
+ 1802,
51
+ 15,
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
+ "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
+ "up_proj",
98
+ "v_proj"
99
+ ]
100
+ },
101
+ "trained_stage": "e16",
102
+ "source_checkpoint": "models/e16/S1-E19-a1-n16k-a100-syn/ckpt-16000",
103
+ "softcap": null,
104
+ "e16": {
105
+ "data": "data/e19/E19-a1-n16k-a100",
106
+ "data_manifest": {
107
+ "arm": "E19-a1-n16k-a100",
108
+ "name": null,
109
+ "train_sha256": "e8630093337aa4e236ec84240be87518ce2f248884bb346f205966a4da98bbe6",
110
+ "n_train": 16000
111
+ },
112
+ "init": "released",
113
+ "objective": "s-log",
114
+ "sigma": 0.5,
115
+ "K": 8,
116
+ "reward": "brier",
117
+ "clip": 0.2,
118
+ "passes": 1,
119
+ "lr": 0.0001,
120
+ "lr_head": 0.0002,
121
+ "rows_per_step": 32,
122
+ "train_seed": 0,
123
+ "replay": "data/e16/replay/train.jsonl",
124
+ "replay_frac": 0.05,
125
+ "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e",
126
+ "max_len": 3072,
127
+ "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps",
128
+ "total_rows": 16000,
129
+ "lora": {
130
+ "r": 16,
131
+ "lora_alpha": 32,
132
+ "lora_dropout": 0.05
133
+ },
134
+ "trainer_sha256": "bc7c08e836bd99bb2665b02903cd41404ea029ecfa9b68a9ec1a7cda96958ba4",
135
+ "event": "ckpt",
136
+ "tag": "ckpt-16000",
137
+ "rows_seen": 16000,
138
+ "replay_seen": 842,
139
+ "step": 500,
140
+ "tokens": 8943984,
141
+ "tok_per_s": 800.2291356549823,
142
+ "rows_per_s": 1.506874240361042,
143
+ "val": {
144
+ "n": 1200,
145
+ "dropped_long": 0,
146
+ "noul_ce": 0.6381511092185974,
147
+ "noul_T": 1.029952342237469,
148
+ "choice_ce": 0.6812111735343933,
149
+ "choice_T": 1.0577606522158263,
150
+ "score_ce": 1.0487253665924072,
151
+ "score_T": 0.9693892850617055,
152
+ "noul_auc": 0.7012010666666667,
153
+ "noul_acc": 0.623,
154
+ "noul_f1": 0.6606660666066607,
155
+ "noul_nll": 0.6497219701781869,
156
+ "noul_ece": 0.15711297784745692,
157
+ "noul_brier": 0.22903177858235785,
158
+ "noul_sharp": 0.11895649135112762,
159
+ "entropy": 0.6470414400100708
160
+ },
161
+ "dropped_long": 0,
162
+ "peak_gib": 18.235705852508545
163
+ }
164
+ }
e16/S1-E19-a1-n16k-a100-syn/train_log.jsonl ADDED
@@ -0,0 +1,57 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"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}
2
+ {"time": "10:26:31", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 832.215934471425, "loss": 0.6503720320761204, "entropy": 0.5711615234613419, "sharp": 0.18100939877331257}
3
+ {"time": "10:30:04", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 835.3748754877928, "loss": 0.7035536766052246, "entropy": 0.6894180849194527, "sharp": 0.034258763305842876}
4
+ {"time": "10:33:27", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 838.9595970088511, "loss": 0.6800523512065411, "entropy": 0.5931671634316444, "sharp": 0.21896221209317446}
5
+ {"time": "10:36:59", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 842.815763961821, "loss": 0.6651643253862858, "entropy": 0.6212584301829338, "sharp": 0.1841421201825142}
6
+ {"time": "10:40:30", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 844.9477148634276, "loss": 0.8803777396678925, "entropy": 0.5221148766577244, "sharp": 0.2714403895661235}
7
+ {"time": "10:44:05", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 846.8398017550991, "loss": 0.5903759626671672, "entropy": 0.6428889781236649, "sharp": 0.15241909213364124}
8
+ {"time": "10:47:31", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 846.2101719978011, "loss": 0.5371279790997505, "entropy": 0.625563457608223, "sharp": 0.14285138621926308}
9
+ {"time": "10:51:02", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 846.7297082415794, "loss": 0.5095812827348709, "entropy": 0.6165564339607954, "sharp": 0.17431860882788897}
10
+ {"time": "10:54:43", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 847.0694888589081, "loss": 0.5790985561907291, "entropy": 0.5464204847812653, "sharp": 0.23400881234556437}
11
+ {"time": "10:58:11", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 846.8619857013724, "loss": 0.6190801188349724, "entropy": 0.5829369276762009, "sharp": 0.204022865742445}
12
+ {"time": "10:59:39", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.6026919484138489, "noul_T": 0.9985054403162195, "noul_auc": 0.723025771716933, "noul_acc": 0.696, "noul_f1": 0.7516339869281046, "noul_nll": 0.6028332934379578, "noul_ece": 0.08748101645708084, "noul_brier": 0.2066839419229499, "noul_sharp": 0.18342091143131256, "entropy": 0.6030364036560059}
13
+ {"time": "11:03:13", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 815.8798989024405, "loss": 0.6510646883398294, "entropy": 0.5296716243028641, "sharp": 0.2527691125869751}
14
+ {"time": "11:06:45", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 818.205485309743, "loss": 0.6181143224239349, "entropy": 0.6208961382508278, "sharp": 0.15619943849742413}
15
+ {"time": "11:10:20", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 820.515999020221, "loss": 0.5577158182859421, "entropy": 0.6032292917370796, "sharp": 0.17383813671767712}
16
+ {"time": "11:13:56", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 822.4567253191066, "loss": 0.5824116636067629, "entropy": 0.5780835635960102, "sharp": 0.20110554620623589}
17
+ {"time": "11:17:32", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 823.8366029342371, "loss": 0.5870324000716209, "entropy": 0.5703915953636169, "sharp": 0.22162242233753204}
18
+ {"time": "11:21:06", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 825.3793335940491, "loss": 0.5691555878147483, "entropy": 0.5476700067520142, "sharp": 0.25301511213183403}
19
+ {"time": "11:24:39", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 826.387685388931, "loss": 0.6594888791441917, "entropy": 0.5493587926030159, "sharp": 0.23202674090862274}
20
+ {"time": "11:28:13", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 827.6791375822697, "loss": 0.45203861221671104, "entropy": 0.5760078802704811, "sharp": 0.21370270289480686}
21
+ {"time": "11:31:42", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 828.775444930111, "loss": 0.4263534629717469, "entropy": 0.5652435384690762, "sharp": 0.2145265731960535}
22
+ {"time": "11:35:17", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 829.9704047498159, "loss": 0.6323573105037212, "entropy": 0.5215331017971039, "sharp": 0.25061337277293205}
23
+ {"time": "11:36:45", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.7070821523666382, "noul_T": 2.607318523164162, "noul_auc": 0.6837690503113871, "noul_acc": 0.576, "noul_f1": 0.5725806451612904, "noul_nll": 0.6949131693169475, "noul_ece": 0.19022765171527864, "noul_brier": 0.24933418391212944, "noul_sharp": 0.13735003769397736, "entropy": 0.6294962763786316}
24
+ {"time": "11:40:11", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 814.5729680080522, "loss": 0.5041964033152908, "entropy": 0.54010427929461, "sharp": 0.24342864658683538}
25
+ {"time": "11:43:41", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 816.044691468237, "loss": 0.6632502619177103, "entropy": 0.595496354624629, "sharp": 0.19346865080296993}
26
+ {"time": "11:47:14", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 817.4013498744666, "loss": 0.5497537031769753, "entropy": 0.5058524012565613, "sharp": 0.25955813378095627}
27
+ {"time": "11:50:44", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 818.3953394499622, "loss": 0.5206624902784824, "entropy": 0.5650177896022797, "sharp": 0.22011052072048187}
28
+ {"time": "11:54:21", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 818.902714274178, "loss": 0.6027582138776779, "entropy": 0.5734657794237137, "sharp": 0.20418879389762878}
29
+ {"time": "11:57:48", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 819.8711681602891, "loss": 0.582035715226084, "entropy": 0.4800318330526352, "sharp": 0.28131208941340446}
30
+ {"time": "12:01:13", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 820.7199643115657, "loss": 0.5497518759220839, "entropy": 0.6182224117219448, "sharp": 0.1632665190845728}
31
+ {"time": "12:04:53", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 821.9872993392887, "loss": 0.5552526749670506, "entropy": 0.600985124707222, "sharp": 0.18093677423894405}
32
+ {"time": "12:08:17", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 823.0906642841982, "loss": 0.5772420540452003, "entropy": 0.5172719657421112, "sharp": 0.261272668838501}
33
+ {"time": "12:11:49", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 823.8119914514645, "loss": 0.6288931090384722, "entropy": 0.6425002608448267, "sharp": 0.12107713799923658}
34
+ {"time": "12:13:17", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.6300765872001648, "noul_T": 0.5641575143935115, "noul_auc": 0.7005113837741135, "noul_acc": 0.684, "noul_f1": 0.742671009771987, "noul_nll": 0.6282359160482883, "noul_ece": 0.10625261414051057, "noul_brier": 0.2184704393580207, "noul_sharp": 0.09788722544908524, "entropy": 0.6657898426055908}
35
+ {"time": "12:16:38", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 813.8181990496638, "loss": 0.6217633411288261, "entropy": 0.6106591522693634, "sharp": 0.17323236912488937}
36
+ {"time": "12:20:01", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 814.670081320438, "loss": 0.6677860468626022, "entropy": 0.5611538887023926, "sharp": 0.22135654091835022}
37
+ {"time": "12:23:29", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 815.8281520106739, "loss": 0.6287044901400805, "entropy": 0.4863416440784931, "sharp": 0.2717239446938038}
38
+ {"time": "12:27:05", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 816.9355133598575, "loss": 0.5834899470210075, "entropy": 0.552046649158001, "sharp": 0.2202904187142849}
39
+ {"time": "12:30:27", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 817.9634898548093, "loss": 0.5206081196665764, "entropy": 0.552464809268713, "sharp": 0.22253237292170525}
40
+ {"time": "12:34:08", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 818.8537966389988, "loss": 0.49824991822242737, "entropy": 0.540007758885622, "sharp": 0.22444947436451912}
41
+ {"time": "12:37:41", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 819.7461320756281, "loss": 0.5261658243834972, "entropy": 0.5358233228325844, "sharp": 0.23015872202813625}
42
+ {"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}
43
+ {"time": "12:44:29", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 821.1772794456665, "loss": 0.4678148231469095, "entropy": 0.5416636019945145, "sharp": 0.22772100288420916}
44
+ {"time": "12:47:56", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 821.9935936442631, "loss": 0.5432258527725935, "entropy": 0.48394267726689577, "sharp": 0.2772157145664096}
45
+ {"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}
46
+ {"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}
47
+ {"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}
48
+ {"time": "13:00:00", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 816.2574234521925, "loss": 0.5267088999971747, "entropy": 0.5376625880599022, "sharp": 0.23282405734062195}
49
+ {"time": "13:03:33", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 816.6075526160726, "loss": 0.6298979036509991, "entropy": 0.5059014093130827, "sharp": 0.27642867527902126}
50
+ {"time": "13:07:07", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 817.514755423971, "loss": 0.4871196635067463, "entropy": 0.5451572798192501, "sharp": 0.23542554676532745}
51
+ {"time": "13:10:35", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 817.9885595654318, "loss": 0.5189292952418327, "entropy": 0.5577503703534603, "sharp": 0.2263322975486517}
52
+ {"time": "13:14:00", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 818.5885594405482, "loss": 0.7248121611773968, "entropy": 0.5662439949810505, "sharp": 0.21394966915249825}
53
+ {"time": "13:17:32", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 819.258972805518, "loss": 0.568549009039998, "entropy": 0.5418598055839539, "sharp": 0.2290923986583948}
54
+ {"time": "13:21:04", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 820.0843010722512, "loss": 0.34664853755384684, "entropy": 0.5586813353002071, "sharp": 0.22262434288859367}
55
+ {"time": "13:24:39", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 820.5237510309239, "loss": 0.5983148724772036, "entropy": 0.5489839129149914, "sharp": 0.22317792102694511}
56
+ {"time": "13:26:07", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.6579700708389282, "noul_T": 1.2135891261448262, "noul_auc": 0.7154815952473376, "noul_acc": 0.63, "noul_f1": 0.6489563567362429, "noul_nll": 0.6520484886020422, "noul_ece": 0.1714279436469078, "noul_brier": 0.23002566455107015, "noul_sharp": 0.1269138753414154, "entropy": 0.6419970989227295}
57
+ {"time": "13:29:17", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 8943984, "tok_per_s": 800.2291356549823, "rows_per_s": 1.506874240361042, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.6381511092185974, "noul_T": 1.029952342237469, "choice_ce": 0.6812111735343933, "choice_T": 1.0577606522158263, "score_ce": 1.0487253665924072, "score_T": 0.9693892850617055, "noul_auc": 0.7012010666666667, "noul_acc": 0.623, "noul_f1": 0.6606660666066607, "noul_nll": 0.6497219701781869, "noul_ece": 0.15711297784745692, "noul_brier": 0.22903177858235785, "noul_sharp": 0.11895649135112762, "entropy": 0.6470414400100708}, "dropped_long": 0, "peak_gib": 18.235705852508545}