Unggi commited on
Commit
ddc90dc
·
verified ·
1 Parent(s): 125b519

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

Browse files
e16/S1-E19-a1-n16k-soft-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-soft-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
+ "in_proj_qkv",
40
+ "down_proj",
41
+ "q_proj",
42
+ "out_proj",
43
+ "in_proj_z",
44
+ "v_proj",
45
+ "o_proj",
46
+ "gate_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
+ }
e16/S1-E19-a1-n16k-soft-a100-syn/ckpt-16000/adapter/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:49d4573e5a94df870f77126a3dce9abe8c047a6eefb604b20a3d0f3ab0719794
3
+ size 160486456
e16/S1-E19-a1-n16k-soft-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-soft-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 sha256:15e7fe1750d6ebd0f6c036a2c8977354c0bf5493aff3d62e746713af834ad88c
3
+ size 176641832
e16/S1-E19-a1-n16k-soft-a100-syn/ckpt-16000/adapter_vllm/decision_head.json ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bias": [
3
+ 0.0006658267229795456,
4
+ -0.0006660837680101395,
5
+ -0.0022681518457829952,
6
+ -0.0012672654120251536,
7
+ -0.00044467038242146373,
8
+ 0.0018637655302882195,
9
+ 0.001113274833187461,
10
+ -0.0023357649333775043,
11
+ -0.0004471878055483103,
12
+ -0.00019837715080939233,
13
+ 5.3723335440736264e-05,
14
+ 0.0004352069809101522,
15
+ -0.00019835689454339445,
16
+ -0.0034517450258135796,
17
+ -0.004249265417456627,
18
+ -0.005067416932433844,
19
+ -0.005925778765231371,
20
+ -0.004341768566519022,
21
+ -0.0049264864064753056,
22
+ -0.004925806075334549,
23
+ -0.0038481371011584997,
24
+ -0.003338830778375268,
25
+ -0.005609303712844849,
26
+ -0.003459909465163946
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-soft-a100-syn/ckpt-16000/calibration.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "version": 1,
3
+ "per_kind": {
4
+ "noul": 0.9114489262835489,
5
+ "choice": 1.057254374772595,
6
+ "score": 0.9152068187959267
7
+ },
8
+ "fit": {
9
+ "noul": {
10
+ "n": 1087,
11
+ "T": 0.9114489262835489,
12
+ "ce_before": 0.6224223375320435,
13
+ "ce_after": 0.6220250129699707
14
+ },
15
+ "choice": {
16
+ "n": 60,
17
+ "T": 1.057254374772595,
18
+ "ce_before": 0.6652951836585999,
19
+ "ce_after": 0.6645907759666443
20
+ },
21
+ "score": {
22
+ "n": 53,
23
+ "T": 0.9152068187959267,
24
+ "ce_before": 1.0459662675857544,
25
+ "ce_after": 1.0437508821487427
26
+ }
27
+ },
28
+ "source": "models/e16/S1-E19-a1-n16k-soft-a100-syn/ckpt-16000"
29
+ }
e16/S1-E19-a1-n16k-soft-a100-syn/ckpt-16000/head.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca3b3463fd64e184a919b16e233b3ecbacb5fa161270834bd4b9a99e0f1eb6db
3
+ size 393464
e16/S1-E19-a1-n16k-soft-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-soft-a100-syn/ckpt-16000",
103
+ "softcap": null,
104
+ "e16": {
105
+ "data": "data/e19/E19-a1-n16k-soft-a100",
106
+ "data_manifest": {
107
+ "arm": "E19-a1-n16k-soft-a100",
108
+ "name": null,
109
+ "train_sha256": "26c76407ec87e34f18ef4d716b29e42a18588832bf6066becc156828e266fd8d",
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": 799.8102136880569,
142
+ "rows_per_s": 1.5060853878070437,
143
+ "val": {
144
+ "n": 1200,
145
+ "dropped_long": 0,
146
+ "noul_ce": 0.6224223375320435,
147
+ "noul_T": 0.9114489262835489,
148
+ "choice_ce": 0.6652951836585999,
149
+ "choice_T": 1.057254374772595,
150
+ "score_ce": 1.0459662675857544,
151
+ "score_T": 0.9152068187959267,
152
+ "noul_auc": 0.7117696,
153
+ "noul_acc": 0.655,
154
+ "noul_f1": 0.7048759623609923,
155
+ "noul_nll": 0.6312288008481264,
156
+ "noul_ece": 0.13414508992433546,
157
+ "noul_brier": 0.22015866136246331,
158
+ "noul_sharp": 0.12622646987438202,
159
+ "entropy": 0.6429359316825867
160
+ },
161
+ "dropped_long": 0,
162
+ "peak_gib": 18.235705852508545
163
+ }
164
+ }
e16/S1-E19-a1-n16k-soft-a100-syn/train_log.jsonl ADDED
@@ -0,0 +1,57 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"time": "11:42:52", "event": "start", "data": "data/e19/E19-a1-n16k-soft-a100", "data_manifest": {"arm": "E19-a1-n16k-soft-a100", "name": null, "train_sha256": "26c76407ec87e34f18ef4d716b29e42a18588832bf6066becc156828e266fd8d", "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": 87.39138960838318}
2
+ {"time": "11:46:24", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 833.045002964947, "loss": 0.588922917842865, "entropy": 0.6021130159497261, "sharp": 0.17588666453957558}
3
+ {"time": "11:49:56", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 838.5924052389523, "loss": 0.6846533715724945, "entropy": 0.6910380870103836, "sharp": 0.02306802850216627}
4
+ {"time": "11:53:18", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 841.6301510007838, "loss": 0.6661521978676319, "entropy": 0.5978059396147728, "sharp": 0.20922003965824842}
5
+ {"time": "11:56:50", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 844.8019385424639, "loss": 0.672111114487052, "entropy": 0.5462029725313187, "sharp": 0.2420680020004511}
6
+ {"time": "12:00:21", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 847.1717991932633, "loss": 0.6684608198702335, "entropy": 0.6568677686154842, "sharp": 0.11821198370307684}
7
+ {"time": "12:03:56", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 848.6487143984357, "loss": 0.552405945956707, "entropy": 0.5897898375988007, "sharp": 0.20209896843880415}
8
+ {"time": "12:07:22", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 847.7344429147342, "loss": 0.5188641361892223, "entropy": 0.6364869475364685, "sharp": 0.13697880692780018}
9
+ {"time": "12:10:53", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 847.9683708874908, "loss": 0.6211176682263613, "entropy": 0.620494456961751, "sharp": 0.14520255476236343}
10
+ {"time": "12:14:33", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 848.5730778642486, "loss": 0.5867630913853645, "entropy": 0.5737877376377583, "sharp": 0.2130492264404893}
11
+ {"time": "12:18:02", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 847.8368070077156, "loss": 0.5943211764097214, "entropy": 0.5628568381071091, "sharp": 0.22679613903164864}
12
+ {"time": "12:19:31", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.5962151885032654, "noul_T": 0.855300576648382, "noul_auc": 0.7396162090091306, "noul_acc": 0.7, "noul_f1": 0.7648902821316614, "noul_nll": 0.5883893258273601, "noul_ece": 0.08294241684675217, "noul_brier": 0.19997528592409883, "noul_sharp": 0.1696518510580063, "entropy": 0.6174163222312927}
13
+ {"time": "12:23:03", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 816.8766375980072, "loss": 0.5991598144173622, "entropy": 0.5670166835188866, "sharp": 0.22352871671319008}
14
+ {"time": "12:26:35", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 819.1960774745488, "loss": 0.585709735751152, "entropy": 0.608031690120697, "sharp": 0.1612020917236805}
15
+ {"time": "12:30:11", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 821.1672654573591, "loss": 0.5629651173949242, "entropy": 0.6097195222973824, "sharp": 0.17390846461057663}
16
+ {"time": "12:33:46", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 823.1869020762318, "loss": 0.5362141355872154, "entropy": 0.6094481460750103, "sharp": 0.18048185296356678}
17
+ {"time": "12:37:22", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 824.6688560820248, "loss": 0.5523114912211895, "entropy": 0.5417928174138069, "sharp": 0.23383033648133278}
18
+ {"time": "12:40:57", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 825.9575083602982, "loss": 0.5794190187007189, "entropy": 0.5382421314716339, "sharp": 0.23697717301547527}
19
+ {"time": "12:44:30", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 826.9842393305223, "loss": 0.6229254510253668, "entropy": 0.41902289167046547, "sharp": 0.30930429697036743}
20
+ {"time": "12:48:03", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 828.370290529386, "loss": 0.49636731296777725, "entropy": 0.6162767820060253, "sharp": 0.1822980809956789}
21
+ {"time": "12:51:33", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 829.2403496425219, "loss": 0.49741293862462044, "entropy": 0.511407520622015, "sharp": 0.27605065517127514}
22
+ {"time": "12:55:09", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 830.2659905522881, "loss": 0.6265465468168259, "entropy": 0.5433985404670238, "sharp": 0.24515043199062347}
23
+ {"time": "12:56:37", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.6342898607254028, "noul_T": 1.1485404335145972, "noul_auc": 0.7080555602437089, "noul_acc": 0.674, "noul_f1": 0.7232597623089984, "noul_nll": 0.617951015740633, "noul_ece": 0.10988062268495559, "noul_brier": 0.21429277833614635, "noul_sharp": 0.16713516414165497, "entropy": 0.6170523762702942}
24
+ {"time": "13:00:02", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 814.9638584856447, "loss": 0.5445428052917123, "entropy": 0.6136729270219803, "sharp": 0.16579995956271887}
25
+ {"time": "13:03:33", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 816.2879168358388, "loss": 0.5680861752480268, "entropy": 0.5633813664317131, "sharp": 0.22864008322358131}
26
+ {"time": "13:07:06", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 817.530963309837, "loss": 0.5666002985090017, "entropy": 0.5461645387113094, "sharp": 0.23473116382956505}
27
+ {"time": "13:10:36", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 818.6152142850999, "loss": 0.586516983807087, "entropy": 0.5211193859577179, "sharp": 0.2518439032137394}
28
+ {"time": "13:14:13", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 819.2063564651986, "loss": 0.5545659437775612, "entropy": 0.5577898062765598, "sharp": 0.2275696061551571}
29
+ {"time": "13:17:40", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 820.062669692517, "loss": 0.46058891993016005, "entropy": 0.5386128015816212, "sharp": 0.24167500436306}
30
+ {"time": "13:21:05", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 820.8843295921346, "loss": 0.5058119799941778, "entropy": 0.565500020980835, "sharp": 0.2239266335964203}
31
+ {"time": "13:24:44", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 822.2322944431492, "loss": 0.5481334328651428, "entropy": 0.6028634607791901, "sharp": 0.17307910695672035}
32
+ {"time": "13:28:09", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 823.2309101721536, "loss": 0.5663433335721493, "entropy": 0.519042007625103, "sharp": 0.2564035151153803}
33
+ {"time": "13:31:41", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 823.8825578679619, "loss": 0.6125295609235764, "entropy": 0.6427918300032616, "sharp": 0.12503604125231504}
34
+ {"time": "13:33:10", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.6368759870529175, "noul_T": 0.5320408028986313, "noul_auc": 0.7128656056437866, "noul_acc": 0.692, "noul_f1": 0.7433333333333333, "noul_nll": 0.6319964309036732, "noul_ece": 0.12918312162160875, "noul_brier": 0.22017683533050206, "noul_sharp": 0.0868634358048439, "entropy": 0.6702858805656433}
35
+ {"time": "13:36:31", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 813.8884628223929, "loss": 0.5843488276004791, "entropy": 0.6127106919884682, "sharp": 0.16960112936794758}
36
+ {"time": "13:39:55", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 814.6310314016416, "loss": 0.7197622507810593, "entropy": 0.5646428242325783, "sharp": 0.21796787530183792}
37
+ {"time": "13:43:24", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 815.6557601710133, "loss": 0.5784352049231529, "entropy": 0.5157584249973297, "sharp": 0.23875261191278696}
38
+ {"time": "13:47:01", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 816.6958798111687, "loss": 0.5721590183675289, "entropy": 0.5801337212324142, "sharp": 0.19855961576104164}
39
+ {"time": "13:50:24", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 817.6024403275716, "loss": 0.6272653751075268, "entropy": 0.5256512351334095, "sharp": 0.24470312520861626}
40
+ {"time": "13:54:06", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 818.4129216282679, "loss": 0.5601907148957253, "entropy": 0.5658868476748466, "sharp": 0.1933346427977085}
41
+ {"time": "13:57:39", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 819.2607180204641, "loss": 0.5955355130136013, "entropy": 0.5704315751791, "sharp": 0.18660753779113293}
42
+ {"time": "14:01:02", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 819.8601798315927, "loss": 0.6904039829969406, "entropy": 0.511899490840733, "sharp": 0.24448657780885696}
43
+ {"time": "14:04:29", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 820.4708968536918, "loss": 0.5958489011973143, "entropy": 0.5645651370286942, "sharp": 0.20982736721634865}
44
+ {"time": "14:07:59", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 821.1821068275964, "loss": 0.5036460254341364, "entropy": 0.5719989649951458, "sharp": 0.20386691577732563}
45
+ {"time": "14:09:27", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.6395184993743896, "noul_T": 0.8266468933649221, "noul_auc": 0.7279370812306966, "noul_acc": 0.67, "noul_f1": 0.7069271758436945, "noul_nll": 0.632122870117426, "noul_ece": 0.1352908192873001, "noul_brier": 0.22041567304821358, "noul_sharp": 0.11165791004896164, "entropy": 0.6533892154693604}
46
+ {"time": "14:12:57", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 813.802433499434, "loss": 0.6287189461290836, "entropy": 0.5764273591339588, "sharp": 0.20393908582627773}
47
+ {"time": "14:16:30", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 814.5731110232023, "loss": 0.6615785881876945, "entropy": 0.5217020995914936, "sharp": 0.2479446791112423}
48
+ {"time": "14:20:02", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 815.497796567564, "loss": 0.6035016844980419, "entropy": 0.5069842571392655, "sharp": 0.26279960945248604}
49
+ {"time": "14:23:34", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 815.9498013257964, "loss": 0.6159990951418877, "entropy": 0.48702458292245865, "sharp": 0.2891466598957777}
50
+ {"time": "14:27:09", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 816.8176237196193, "loss": 0.5535023231059313, "entropy": 0.528935207054019, "sharp": 0.2459303755313158}
51
+ {"time": "14:30:36", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 817.3091180175996, "loss": 0.5377992875874043, "entropy": 0.5508109740912914, "sharp": 0.22673368453979492}
52
+ {"time": "14:34:01", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 818.0065653376412, "loss": 0.6162302289158106, "entropy": 0.5840697642415762, "sharp": 0.1880231313407421}
53
+ {"time": "14:37:33", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 818.673447878204, "loss": 0.5571026224642992, "entropy": 0.5564380884170532, "sharp": 0.20396986231207848}
54
+ {"time": "14:41:05", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 819.497433720899, "loss": 0.43161831982433796, "entropy": 0.5723839905112982, "sharp": 0.2016696110367775}
55
+ {"time": "14:44:39", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 820.0609426459966, "loss": 0.6136300815269351, "entropy": 0.5593843199312687, "sharp": 0.21258223615586758}
56
+ {"time": "14:46:07", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.6427628993988037, "noul_T": 1.046814857769061, "noul_auc": 0.7272788644917385, "noul_acc": 0.668, "noul_f1": 0.7046263345195729, "noul_nll": 0.6316258210390806, "noul_ece": 0.14266333568096162, "noul_brier": 0.22007706664471674, "noul_sharp": 0.1327688843011856, "entropy": 0.6386560201644897}
57
+ {"time": "14:49:17", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 8943984, "tok_per_s": 799.8102136880569, "rows_per_s": 1.5060853878070437, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.6224223375320435, "noul_T": 0.9114489262835489, "choice_ce": 0.6652951836585999, "choice_T": 1.057254374772595, "score_ce": 1.0459662675857544, "score_T": 0.9152068187959267, "noul_auc": 0.7117696, "noul_acc": 0.655, "noul_f1": 0.7048759623609923, "noul_nll": 0.6312288008481264, "noul_ece": 0.13414508992433546, "noul_brier": 0.22015866136246331, "noul_sharp": 0.12622646987438202, "entropy": 0.6429359316825867}, "dropped_long": 0, "peak_gib": 18.235705852508545}