Unggi commited on
Commit
c59a467
·
verified ·
1 Parent(s): e1bbc16

backup e16/S1-ABCLODO16-junyi (Pod B)

Browse files
e16/S1-ABCLODO16-junyi/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-ABCLODO16-junyi/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
+ "down_proj",
39
+ "k_proj",
40
+ "up_proj",
41
+ "in_proj_qkv",
42
+ "o_proj",
43
+ "gate_proj",
44
+ "out_proj",
45
+ "v_proj",
46
+ "q_proj",
47
+ "in_proj_z"
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-ABCLODO16-junyi/ckpt-16000/adapter/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fa2bf3f4c538fbc40fababc67087f752c21f203da200cd9b195f92f9d2c31e8b
3
+ size 160486456
e16/S1-ABCLODO16-junyi/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-ABCLODO16-junyi/ckpt-16000/adapter_vllm/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f48bbdc9ed64a38be26fabcdca495748cce5f16a92fb999031beacc964f9f0b9
3
+ size 176641832
e16/S1-ABCLODO16-junyi/ckpt-16000/adapter_vllm/decision_head.json ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bias": [
3
+ 0.0004060330684296787,
4
+ -0.00040628958959132433,
5
+ -0.00258005247451365,
6
+ -0.0016756807453930378,
7
+ -0.0006792059866711497,
8
+ 0.0019725237507373095,
9
+ 0.0013469189871102571,
10
+ -0.0022389190271496773,
11
+ -0.00018652758444659412,
12
+ -0.00023381681239698082,
13
+ 0.00024248665431514382,
14
+ 0.0008470978937111795,
15
+ 0.0003678629582282156,
16
+ -0.0045778099447488785,
17
+ -0.005782118998467922,
18
+ -0.00566343916580081,
19
+ -0.006171931512653828,
20
+ -0.005448245443403721,
21
+ -0.005534274037927389,
22
+ -0.006028322037309408,
23
+ -0.004884829744696617,
24
+ -0.004546264186501503,
25
+ -0.00651802122592926,
26
+ -0.004450250416994095
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-ABCLODO16-junyi/ckpt-16000/calibration.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "version": 1,
3
+ "per_kind": {
4
+ "noul": 0.8842068581106572,
5
+ "choice": 1.061410127867425,
6
+ "score": 0.9985754156671756
7
+ },
8
+ "fit": {
9
+ "noul": {
10
+ "n": 1802,
11
+ "T": 0.8842068581106572,
12
+ "ce_before": 0.525688111782074,
13
+ "ce_after": 0.5240776538848877
14
+ },
15
+ "choice": {
16
+ "n": 60,
17
+ "T": 1.061410127867425,
18
+ "ce_before": 0.6684281826019287,
19
+ "ce_after": 0.6676441431045532
20
+ },
21
+ "score": {
22
+ "n": 53,
23
+ "T": 0.9985754156671756,
24
+ "ce_before": 1.0547449588775635,
25
+ "ce_after": 1.0547438859939575
26
+ }
27
+ },
28
+ "source": "models/e16/S1-ABCLODO16-junyi/ckpt-16000"
29
+ }
e16/S1-ABCLODO16-junyi/ckpt-16000/head.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:edd39601d20554916ab3cd8d4a89fc1eeaa0723a9f8837977767be3a2e16c5ca
3
+ size 393464
e16/S1-ABCLODO16-junyi/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-ABCLODO16-junyi/ckpt-16000",
103
+ "softcap": null,
104
+ "e16": {
105
+ "data": "data/e15/F1-pool-jev-LODO-junyi",
106
+ "data_manifest": {
107
+ "arm": "F1-pool-jev-LODO-junyi",
108
+ "name": "F1-pool-jev-LODO-junyi",
109
+ "train_sha256": "197a9ae708c4546f360db7bf9e845e2fddbf1c22aa07652ca9009f28d11c828d",
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": 10790962,
141
+ "tok_per_s": 810.3856332115948,
142
+ "rows_per_s": 1.2648098314081313,
143
+ "val": {
144
+ "n": 1915,
145
+ "dropped_long": 0,
146
+ "noul_ce": 0.525688111782074,
147
+ "noul_T": 0.8842068581106572,
148
+ "choice_ce": 0.6684281826019287,
149
+ "choice_T": 1.061410127867425,
150
+ "score_ce": 1.0547449588775635,
151
+ "score_T": 0.9985754156671756,
152
+ "noul_auc": 0.7822765412550756,
153
+ "noul_acc": 0.7381924198250729,
154
+ "noul_f1": 0.8050369083803735,
155
+ "noul_nll": 0.5302975064442214,
156
+ "noul_ece": 0.04533599079002793,
157
+ "noul_brier": 0.1769066334590793,
158
+ "noul_sharp": 0.22304324805736542,
159
+ "entropy": 0.5552073121070862
160
+ },
161
+ "dropped_long": 0,
162
+ "peak_gib": 18.236003398895264
163
+ }
164
+ }
e16/S1-ABCLODO16-junyi/train_log.jsonl ADDED
@@ -0,0 +1,57 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"time": "02:23:51", "event": "start", "data": "data/e15/F1-pool-jev-LODO-junyi", "data_manifest": {"arm": "F1-pool-jev-LODO-junyi", "name": "F1-pool-jev-LODO-junyi", "train_sha256": "197a9ae708c4546f360db7bf9e845e2fddbf1c22aa07652ca9009f28d11c828d", "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": 79.50239443778992}
2
+ {"time": "02:27:59", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 861.8945686470406, "loss": 0.5822928175330162, "entropy": 0.5668162405490875, "sharp": 0.21648880653083324}
3
+ {"time": "02:32:12", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 864.1169644063198, "loss": 0.6113677490502596, "entropy": 0.5817635841667652, "sharp": 0.1980749536305666}
4
+ {"time": "02:36:25", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 865.2610980516926, "loss": 0.546056617051363, "entropy": 0.49664628878235817, "sharp": 0.27341744862496853}
5
+ {"time": "02:40:34", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 865.6448583656367, "loss": 0.5860969433560967, "entropy": 0.6454560235142708, "sharp": 0.13622043281793594}
6
+ {"time": "02:44:45", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 866.712315613865, "loss": 0.6407751813530922, "entropy": 0.5314248874783516, "sharp": 0.2486370261758566}
7
+ {"time": "02:48:53", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 866.329986608656, "loss": 0.5813371334224939, "entropy": 0.5541219525039196, "sharp": 0.21569320745766163}
8
+ {"time": "02:53:04", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 867.1717739728908, "loss": 0.5668085692450404, "entropy": 0.5705241598188877, "sharp": 0.19117500446736813}
9
+ {"time": "02:57:14", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 866.1835896495695, "loss": 0.5840453682467341, "entropy": 0.5577344503253698, "sharp": 0.22707732394337654}
10
+ {"time": "03:01:24", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 866.9249081639184, "loss": 0.6424346081912518, "entropy": 0.5931721851229668, "sharp": 0.19342203065752983}
11
+ {"time": "03:05:27", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 866.9027136032821, "loss": 0.5604449585080147, "entropy": 0.542963445186615, "sharp": 0.2308657243847847}
12
+ {"time": "03:07:14", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.5468561053276062, "noul_T": 0.9554732719322565, "noul_auc": 0.7613974758933636, "noul_acc": 0.724, "noul_f1": 0.7952522255192879, "noul_nll": 0.5468561245501041, "noul_ece": 0.054456783533096326, "noul_brier": 0.18395632649809218, "noul_sharp": 0.2241920828819275, "entropy": 0.5563964247703552}
13
+ {"time": "03:11:13", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 834.6521411779086, "loss": 0.520088973455131, "entropy": 0.5855270512402058, "sharp": 0.2014442514628172}
14
+ {"time": "03:15:23", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 837.1402330988045, "loss": 0.5927688190713525, "entropy": 0.5455445125699043, "sharp": 0.23785529285669327}
15
+ {"time": "03:19:33", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 839.835311946561, "loss": 0.6025742162019014, "entropy": 0.5676053166389465, "sharp": 0.2166642788797617}
16
+ {"time": "03:23:45", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 841.9382902321998, "loss": 0.5269198147580028, "entropy": 0.5301808137446642, "sharp": 0.24988807551562786}
17
+ {"time": "03:27:50", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 843.7575026945773, "loss": 0.6579915611073375, "entropy": 0.5676995366811752, "sharp": 0.20884225703775883}
18
+ {"time": "03:31:46", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 845.6409071213146, "loss": 0.6028530416078866, "entropy": 0.6006355881690979, "sharp": 0.17812272533774376}
19
+ {"time": "03:36:02", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 847.0079929065042, "loss": 0.6091933101415634, "entropy": 0.5488564185798168, "sharp": 0.23336135782301426}
20
+ {"time": "03:40:14", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 848.5369607537957, "loss": 0.6066305786371231, "entropy": 0.6014931872487068, "sharp": 0.1790844053030014}
21
+ {"time": "03:44:15", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 849.7493541917063, "loss": 0.5284620597958565, "entropy": 0.5154511732980609, "sharp": 0.2547400761395693}
22
+ {"time": "03:48:23", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 850.9934233983348, "loss": 0.6364323236048222, "entropy": 0.5619666054844856, "sharp": 0.22364382818341255}
23
+ {"time": "03:50:09", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.5687510371208191, "noul_T": 0.9648769759200664, "noul_auc": 0.7526588201928531, "noul_acc": 0.7, "noul_f1": 0.7685185185185185, "noul_nll": 0.568751022130251, "noul_ece": 0.09915343564748763, "noul_brier": 0.1928656403169509, "noul_sharp": 0.20651812851428986, "entropy": 0.5754334926605225}
24
+ {"time": "03:54:12", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 835.3277332377992, "loss": 0.5938563477247953, "entropy": 0.5108351968228817, "sharp": 0.2534559592604637}
25
+ {"time": "03:58:12", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 836.7732821267799, "loss": 0.5226390864700079, "entropy": 0.5677602365612984, "sharp": 0.21863808948546648}
26
+ {"time": "04:02:16", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 838.2536934250711, "loss": 0.5353064779192209, "entropy": 0.5346648432314396, "sharp": 0.23874379135668278}
27
+ {"time": "04:06:21", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 839.5969220129089, "loss": 0.5560992732644081, "entropy": 0.5339225567877293, "sharp": 0.2389255203306675}
28
+ {"time": "04:10:31", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 840.8310584973999, "loss": 0.604085536673665, "entropy": 0.5917456708848476, "sharp": 0.17668969184160233}
29
+ {"time": "04:14:39", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 841.7338427800462, "loss": 0.5314682964235544, "entropy": 0.5256273522973061, "sharp": 0.26422782987356186}
30
+ {"time": "04:18:53", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 842.7544382107161, "loss": 0.5636822506785393, "entropy": 0.5851416438817978, "sharp": 0.2044214140623808}
31
+ {"time": "04:23:02", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 843.453169903403, "loss": 0.5907248333096504, "entropy": 0.5872385427355766, "sharp": 0.1950840037316084}
32
+ {"time": "04:27:10", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 844.3876325034504, "loss": 0.6026761904358864, "entropy": 0.5689888671040535, "sharp": 0.2161649949848652}
33
+ {"time": "04:31:21", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 845.3338205059387, "loss": 0.6366631342098117, "entropy": 0.5311114266514778, "sharp": 0.23460775054991245}
34
+ {"time": "04:33:07", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5480237603187561, "noul_T": 1.0329937292191684, "noul_auc": 0.7553353658536583, "noul_acc": 0.728, "noul_f1": 0.8, "noul_nll": 0.5480237356498837, "noul_ece": 0.057239197373390185, "noul_brier": 0.1849460647297483, "noul_sharp": 0.23241259157657623, "entropy": 0.5411527156829834}
35
+ {"time": "04:37:07", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 834.9014047948281, "loss": 0.5673371069133282, "entropy": 0.5862594768404961, "sharp": 0.19777599070221186}
36
+ {"time": "04:41:13", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 835.8013567166626, "loss": 0.5706391111016273, "entropy": 0.5376488761976361, "sharp": 0.23273520823568106}
37
+ {"time": "04:45:29", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 837.0863893561082, "loss": 0.5750464089214802, "entropy": 0.5803776681423187, "sharp": 0.19455552008002996}
38
+ {"time": "04:49:34", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 838.1116167135067, "loss": 0.6006006971001625, "entropy": 0.5727469399571419, "sharp": 0.2039149459451437}
39
+ {"time": "04:53:46", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 839.010121649566, "loss": 0.5604831771925092, "entropy": 0.6054116301238537, "sharp": 0.17875684052705765}
40
+ {"time": "04:57:53", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 839.8982247886945, "loss": 0.6535944044589996, "entropy": 0.582423928193748, "sharp": 0.19295069575309753}
41
+ {"time": "05:02:06", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 840.5526463191751, "loss": 0.5708425901830196, "entropy": 0.5720285642892122, "sharp": 0.2118510939180851}
42
+ {"time": "05:06:12", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 841.3549520016547, "loss": 0.6336799710988998, "entropy": 0.548972811549902, "sharp": 0.21409549564123154}
43
+ {"time": "05:10:21", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 841.9972173173538, "loss": 0.6023753909394145, "entropy": 0.5769018419086933, "sharp": 0.2012409996241331}
44
+ {"time": "05:14:30", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 842.5702100276899, "loss": 0.534514769911766, "entropy": 0.5551084000617266, "sharp": 0.22739925794303417}
45
+ {"time": "05:16:16", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5575965046882629, "noul_T": 0.9506304570368671, "noul_auc": 0.7480679239931934, "noul_acc": 0.718, "noul_f1": 0.7866868381240545, "noul_nll": 0.5575965000391007, "noul_ece": 0.06978938460350038, "noul_brier": 0.18867784985747726, "noul_sharp": 0.21188919246196747, "entropy": 0.5673142671585083}
46
+ {"time": "05:20:23", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 834.6407795020344, "loss": 0.5893609151244164, "entropy": 0.5535970367491245, "sharp": 0.21820158138871193}
47
+ {"time": "05:24:33", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 835.4367959593764, "loss": 0.5951523296535015, "entropy": 0.5406439416110516, "sharp": 0.22715690173208714}
48
+ {"time": "05:28:40", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 836.1987974757991, "loss": 0.6280372105538845, "entropy": 0.5777122229337692, "sharp": 0.2075652740895748}
49
+ {"time": "05:32:50", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 836.8273115695388, "loss": 0.625586798414588, "entropy": 0.623547051101923, "sharp": 0.15258438512682915}
50
+ {"time": "05:37:01", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 837.6141499990014, "loss": 0.6012628115713596, "entropy": 0.6069367248564959, "sharp": 0.17020337004214525}
51
+ {"time": "05:41:13", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 838.1555117316773, "loss": 0.6108899861574173, "entropy": 0.5412356071174145, "sharp": 0.23334374465048313}
52
+ {"time": "05:45:25", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 838.9005481888784, "loss": 0.6107395421713591, "entropy": 0.583651851862669, "sharp": 0.1866116039454937}
53
+ {"time": "05:49:34", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 839.52076832523, "loss": 0.5951862558722496, "entropy": 0.5887126866728067, "sharp": 0.18740698508918285}
54
+ {"time": "05:53:38", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 840.0840103124519, "loss": 0.5739605166018009, "entropy": 0.5562566202133894, "sharp": 0.22167174145579338}
55
+ {"time": "05:57:49", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 840.5772785726444, "loss": 0.594438225030899, "entropy": 0.550371129065752, "sharp": 0.23362051788717508}
56
+ {"time": "05:59:35", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5516188740730286, "noul_T": 0.9832049310755115, "noul_auc": 0.7525170164492342, "noul_acc": 0.73, "noul_f1": 0.7988077496274217, "noul_nll": 0.5516189115345478, "noul_ece": 0.06776857161521913, "noul_brier": 0.18608310948920354, "noul_sharp": 0.2228119820356369, "entropy": 0.5551533102989197}
57
+ {"time": "06:05:49", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 10790962, "tok_per_s": 810.3856332115948, "rows_per_s": 1.2648098314081313, "val": {"n": 1915, "dropped_long": 0, "noul_ce": 0.525688111782074, "noul_T": 0.8842068581106572, "choice_ce": 0.6684281826019287, "choice_T": 1.061410127867425, "score_ce": 1.0547449588775635, "score_T": 0.9985754156671756, "noul_auc": 0.7822765412550756, "noul_acc": 0.7381924198250729, "noul_f1": 0.8050369083803735, "noul_nll": 0.5302975064442214, "noul_ece": 0.04533599079002793, "noul_brier": 0.1769066334590793, "noul_sharp": 0.22304324805736542, "entropy": 0.5552073121070862}, "dropped_long": 0, "peak_gib": 18.236003398895264}