Gege24 commited on
Commit
96d60e1
·
verified ·
1 Parent(s): dd40b7a

Upload task output 1

Browse files
README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: None
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:/cache/models/Qwen--Qwen2.5-3B-Instruct
7
+ - grpo
8
+ - lora
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- 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. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ 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).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.18.1
adapter_config.json CHANGED
@@ -9,35 +9,35 @@
9
  "ensure_weight_tying": false,
10
  "eva_config": null,
11
  "exclude_modules": null,
12
- "fan_in_fan_out": null,
13
- "inference_mode": false,
14
  "init_lora_weights": true,
15
  "layer_replication": null,
16
  "layers_pattern": null,
17
  "layers_to_transform": null,
18
  "loftq_config": {},
19
- "lora_alpha": 32,
20
  "lora_bias": false,
21
- "lora_dropout": 0.0,
22
  "megatron_config": null,
23
  "megatron_core": "megatron.core",
24
  "modules_to_save": null,
25
  "peft_type": "LORA",
26
  "peft_version": "0.18.1",
27
  "qalora_group_size": 16,
28
- "r": 64,
29
  "rank_pattern": {},
30
  "revision": null,
31
  "target_modules": [
32
- "up_proj",
33
  "v_proj",
34
- "q_proj",
35
- "gate_proj",
36
  "k_proj",
 
37
  "o_proj",
 
38
  "down_proj"
39
  ],
40
- "target_parameters": [],
41
  "task_type": "CAUSAL_LM",
42
  "trainable_token_indices": null,
43
  "use_dora": false,
 
9
  "ensure_weight_tying": false,
10
  "eva_config": null,
11
  "exclude_modules": null,
12
+ "fan_in_fan_out": false,
13
+ "inference_mode": true,
14
  "init_lora_weights": true,
15
  "layer_replication": null,
16
  "layers_pattern": null,
17
  "layers_to_transform": null,
18
  "loftq_config": {},
19
+ "lora_alpha": 256,
20
  "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
  "megatron_config": null,
23
  "megatron_core": "megatron.core",
24
  "modules_to_save": null,
25
  "peft_type": "LORA",
26
  "peft_version": "0.18.1",
27
  "qalora_group_size": 16,
28
+ "r": 128,
29
  "rank_pattern": {},
30
  "revision": null,
31
  "target_modules": [
 
32
  "v_proj",
33
+ "up_proj",
 
34
  "k_proj",
35
+ "gate_proj",
36
  "o_proj",
37
+ "q_proj",
38
  "down_proj"
39
  ],
40
+ "target_parameters": null,
41
  "task_type": "CAUSAL_LM",
42
  "trainable_token_indices": null,
43
  "use_dora": false,
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8770f625ea3546b7a1ccec5ee214f397ae1e299ec3812d8981bb4a76c17c241d
3
+ size 957942768
chat_template.jinja CHANGED
@@ -1,5 +1,54 @@
1
- {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
2
-
3
- '+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
4
-
5
- ' }}{% endif %}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
loss.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ 8,-0.56
special_tokens_map.json CHANGED
@@ -14,13 +14,6 @@
14
  "<|image_pad|>",
15
  "<|video_pad|>"
16
  ],
17
- "bos_token": {
18
- "content": "<|im_end|>",
19
- "lstrip": false,
20
- "normalized": false,
21
- "rstrip": false,
22
- "single_word": false
23
- },
24
  "eos_token": {
25
  "content": "<|im_end|>",
26
  "lstrip": false,
 
14
  "<|image_pad|>",
15
  "<|video_pad|>"
16
  ],
 
 
 
 
 
 
 
17
  "eos_token": {
18
  "content": "<|im_end|>",
19
  "lstrip": false,
tokenizer_config.json CHANGED
@@ -194,7 +194,7 @@
194
  "<|image_pad|>",
195
  "<|video_pad|>"
196
  ],
197
- "bos_token": "<|im_end|>",
198
  "clean_up_tokenization_spaces": false,
199
  "eos_token": "<|im_end|>",
200
  "errors": "replace",
 
194
  "<|image_pad|>",
195
  "<|video_pad|>"
196
  ],
197
+ "bos_token": null,
198
  "clean_up_tokenization_spaces": false,
199
  "eos_token": "<|im_end|>",
200
  "errors": "replace",
trainer_state.json ADDED
@@ -0,0 +1,354 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.0,
6
+ "eval_steps": 500,
7
+ "global_step": 8,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "clip_ratio/high_max": 0.0,
14
+ "clip_ratio/high_mean": 0.0,
15
+ "clip_ratio/low_mean": 0.0,
16
+ "clip_ratio/low_min": 0.0,
17
+ "clip_ratio/region_mean": 0.0,
18
+ "completions/clipped_ratio": 0.0,
19
+ "completions/max_length": 3.0,
20
+ "completions/max_terminated_length": 3.0,
21
+ "completions/mean_length": 2.407738208770752,
22
+ "completions/mean_terminated_length": 2.407738208770752,
23
+ "completions/min_length": 2.0,
24
+ "completions/min_terminated_length": 2.0,
25
+ "entropy": 0.7712807655334473,
26
+ "epoch": 0.25,
27
+ "frac_reward_zero_std": 0.5297619104385376,
28
+ "grad_norm": 4.7248921394348145,
29
+ "learning_rate": 0.0,
30
+ "loss": 0.0255,
31
+ "num_tokens": 117737.0,
32
+ "reward": 0.4955357313156128,
33
+ "reward_std": 0.4984852075576782,
34
+ "rewards/env_game_reward/mean": 0.4955357015132904,
35
+ "rewards/env_game_reward/std": 0.4984852075576782,
36
+ "sampling/importance_sampling_ratio/max": 2.444530487060547,
37
+ "sampling/importance_sampling_ratio/mean": 0.9743361473083496,
38
+ "sampling/importance_sampling_ratio/min": 0.3661190867424011,
39
+ "sampling/sampling_logp_difference/max": 0.8435878753662109,
40
+ "sampling/sampling_logp_difference/mean": 0.10781625658273697,
41
+ "step": 1,
42
+ "step_time": 86.73120934999952
43
+ },
44
+ {
45
+ "clip_ratio/high_max": 0.0,
46
+ "clip_ratio/high_mean": 0.0,
47
+ "clip_ratio/low_mean": 0.0,
48
+ "clip_ratio/low_min": 0.0,
49
+ "clip_ratio/region_mean": 0.0,
50
+ "completions/clipped_ratio": 0.0,
51
+ "completions/max_length": 41.0,
52
+ "completions/max_terminated_length": 41.0,
53
+ "completions/mean_length": 2.5892858505249023,
54
+ "completions/mean_terminated_length": 2.5892858505249023,
55
+ "completions/min_length": 2.0,
56
+ "completions/min_terminated_length": 2.0,
57
+ "entropy": 0.6681132614612579,
58
+ "epoch": 0.5,
59
+ "frac_reward_zero_std": 0.3988095223903656,
60
+ "grad_norm": 2.0864083766937256,
61
+ "learning_rate": 2.84304e-07,
62
+ "loss": 0.0384,
63
+ "num_tokens": 222599.0,
64
+ "reward": 0.5297619104385376,
65
+ "reward_std": 0.4908183515071869,
66
+ "rewards/env_game_reward/mean": 0.5297619104385376,
67
+ "rewards/env_game_reward/std": 0.4908183515071869,
68
+ "sampling/importance_sampling_ratio/max": 2.3313705921173096,
69
+ "sampling/importance_sampling_ratio/mean": 0.9879763126373291,
70
+ "sampling/importance_sampling_ratio/min": 0.0,
71
+ "sampling/sampling_logp_difference/max": 1.0128240585327148,
72
+ "sampling/sampling_logp_difference/mean": 0.09322669357061386,
73
+ "step": 2,
74
+ "step_time": 49.185698066999976
75
+ },
76
+ {
77
+ "clip_ratio/high_max": 0.010094599798321724,
78
+ "clip_ratio/high_mean": 0.005047299899160862,
79
+ "clip_ratio/low_mean": 0.01141490787267685,
80
+ "clip_ratio/low_min": 0.0053089887369424105,
81
+ "clip_ratio/region_mean": 0.016462208004668355,
82
+ "completions/clipped_ratio": 0.0,
83
+ "completions/max_length": 9.0,
84
+ "completions/max_terminated_length": 9.0,
85
+ "completions/mean_length": 2.267857074737549,
86
+ "completions/mean_terminated_length": 2.267857074737549,
87
+ "completions/min_length": 2.0,
88
+ "completions/min_terminated_length": 2.0,
89
+ "entropy": 0.6272067576646805,
90
+ "epoch": 0.75,
91
+ "frac_reward_zero_std": 0.4583333432674408,
92
+ "grad_norm": 3.2909624576568604,
93
+ "learning_rate": 5.68608e-07,
94
+ "loss": 0.0251,
95
+ "num_tokens": 334913.0,
96
+ "reward": 0.5223214626312256,
97
+ "reward_std": 0.49499765038490295,
98
+ "rewards/env_game_reward/mean": 0.5223214030265808,
99
+ "rewards/env_game_reward/std": 0.49499762058258057,
100
+ "sampling/importance_sampling_ratio/max": 1.6051479578018188,
101
+ "sampling/importance_sampling_ratio/mean": 0.9814748764038086,
102
+ "sampling/importance_sampling_ratio/min": 0.0,
103
+ "sampling/sampling_logp_difference/max": 1.094405174255371,
104
+ "sampling/sampling_logp_difference/mean": 0.07474357634782791,
105
+ "step": 3,
106
+ "step_time": 74.23962842500077
107
+ },
108
+ {
109
+ "clip_ratio/high_max": 0.034161615651100874,
110
+ "clip_ratio/high_mean": 0.023498072754591703,
111
+ "clip_ratio/low_mean": 0.008893569000065327,
112
+ "clip_ratio/low_min": 0.005104166688397527,
113
+ "clip_ratio/region_mean": 0.03239164222031832,
114
+ "completions/clipped_ratio": 0.0,
115
+ "completions/max_length": 3.0,
116
+ "completions/max_terminated_length": 3.0,
117
+ "completions/mean_length": 2.3035714626312256,
118
+ "completions/mean_terminated_length": 2.3035714626312256,
119
+ "completions/min_length": 2.0,
120
+ "completions/min_terminated_length": 2.0,
121
+ "entropy": 0.5872454345226288,
122
+ "epoch": 1.0,
123
+ "frac_reward_zero_std": 0.386904776096344,
124
+ "grad_norm": 1.5831847190856934,
125
+ "learning_rate": 8.529119999999999e-07,
126
+ "loss": 0.0144,
127
+ "num_tokens": 439679.0,
128
+ "reward": 0.5372024178504944,
129
+ "reward_std": 0.4834112823009491,
130
+ "rewards/env_game_reward/mean": 0.5372023582458496,
131
+ "rewards/env_game_reward/std": 0.4834113121032715,
132
+ "sampling/importance_sampling_ratio/max": 2.0064399242401123,
133
+ "sampling/importance_sampling_ratio/mean": 1.0050137042999268,
134
+ "sampling/importance_sampling_ratio/min": 0.48575615882873535,
135
+ "sampling/sampling_logp_difference/max": 0.7220797538757324,
136
+ "sampling/sampling_logp_difference/mean": 0.09695391356945038,
137
+ "step": 4,
138
+ "step_time": 48.50994999100112
139
+ },
140
+ {
141
+ "epoch": 1.0,
142
+ "eval_clip_ratio/high_max": 0.0,
143
+ "eval_clip_ratio/high_mean": 0.0,
144
+ "eval_clip_ratio/low_mean": 0.0,
145
+ "eval_clip_ratio/low_min": 0.0,
146
+ "eval_clip_ratio/region_mean": 0.0,
147
+ "eval_completions/clipped_ratio": 0.0,
148
+ "eval_completions/max_length": 2.9,
149
+ "eval_completions/max_terminated_length": 2.9,
150
+ "eval_completions/mean_length": 2.27,
151
+ "eval_completions/mean_terminated_length": 2.27,
152
+ "eval_completions/min_length": 2.0,
153
+ "eval_completions/min_terminated_length": 2.0,
154
+ "eval_entropy": 0.6556259167194366,
155
+ "eval_frac_reward_zero_std": 0.49,
156
+ "eval_loss": -0.002539175096899271,
157
+ "eval_num_tokens": 439679.0,
158
+ "eval_reward": 0.5225,
159
+ "eval_reward_std": 0.4914883863925934,
160
+ "eval_rewards/env_game_reward/mean": 0.5225,
161
+ "eval_rewards/env_game_reward/std": 0.4914884132146835,
162
+ "eval_runtime": 72.4746,
163
+ "eval_samples_per_second": 2.76,
164
+ "eval_sampling/importance_sampling_ratio/max": 1.344225935935974,
165
+ "eval_sampling/importance_sampling_ratio/mean": 0.9896444308757782,
166
+ "eval_sampling/importance_sampling_ratio/min": 0.7344249868392945,
167
+ "eval_sampling/sampling_logp_difference/max": 0.3614662927389145,
168
+ "eval_sampling/sampling_logp_difference/mean": 0.08291504085063935,
169
+ "eval_steps_per_second": 0.345,
170
+ "step": 4
171
+ },
172
+ {
173
+ "clip_ratio/high_max": 0.015843799337744713,
174
+ "clip_ratio/high_mean": 0.011610739515163004,
175
+ "clip_ratio/low_mean": 0.01242961548268795,
176
+ "clip_ratio/low_min": 0.0023809524718672037,
177
+ "clip_ratio/region_mean": 0.024040354881435633,
178
+ "completions/clipped_ratio": 0.0,
179
+ "completions/max_length": 7.0,
180
+ "completions/max_terminated_length": 7.0,
181
+ "completions/mean_length": 2.372023820877075,
182
+ "completions/mean_terminated_length": 2.372023820877075,
183
+ "completions/min_length": 2.0,
184
+ "completions/min_terminated_length": 2.0,
185
+ "entropy": 0.7024529576301575,
186
+ "epoch": 1.25,
187
+ "frac_reward_zero_std": 0.4345238208770752,
188
+ "grad_norm": 2.5793297290802,
189
+ "learning_rate": 1.137216e-06,
190
+ "loss": 0.0003,
191
+ "num_tokens": 560092.0,
192
+ "reward": 0.5684524178504944,
193
+ "reward_std": 0.48845046758651733,
194
+ "rewards/env_game_reward/mean": 0.5684523582458496,
195
+ "rewards/env_game_reward/std": 0.4884504973888397,
196
+ "sampling/importance_sampling_ratio/max": 2.402831554412842,
197
+ "sampling/importance_sampling_ratio/mean": 0.9943535923957825,
198
+ "sampling/importance_sampling_ratio/min": 0.5057061910629272,
199
+ "sampling/sampling_logp_difference/max": 0.8499932289123535,
200
+ "sampling/sampling_logp_difference/mean": 0.0851290300488472,
201
+ "step": 5,
202
+ "step_time": 79.1233635949975
203
+ },
204
+ {
205
+ "clip_ratio/high_max": 0.02467681560665369,
206
+ "clip_ratio/high_mean": 0.015116185648366809,
207
+ "clip_ratio/low_mean": 0.008386317640542984,
208
+ "clip_ratio/low_min": 0.005376344081014395,
209
+ "clip_ratio/region_mean": 0.02350250235758722,
210
+ "completions/clipped_ratio": 0.0,
211
+ "completions/max_length": 5.0,
212
+ "completions/max_terminated_length": 5.0,
213
+ "completions/mean_length": 2.136904716491699,
214
+ "completions/mean_terminated_length": 2.136904716491699,
215
+ "completions/min_length": 2.0,
216
+ "completions/min_terminated_length": 2.0,
217
+ "entropy": 0.5466470569372177,
218
+ "epoch": 1.5,
219
+ "frac_reward_zero_std": 0.380952388048172,
220
+ "grad_norm": 1.9452687501907349,
221
+ "learning_rate": 1.4215199999999998e-06,
222
+ "loss": 0.0011,
223
+ "num_tokens": 664298.0,
224
+ "reward": 0.4940476417541504,
225
+ "reward_std": 0.49621880054473877,
226
+ "rewards/env_game_reward/mean": 0.494047611951828,
227
+ "rewards/env_game_reward/std": 0.49621880054473877,
228
+ "sampling/importance_sampling_ratio/max": 1.6991724967956543,
229
+ "sampling/importance_sampling_ratio/mean": 0.9933019876480103,
230
+ "sampling/importance_sampling_ratio/min": 0.4511236548423767,
231
+ "sampling/sampling_logp_difference/max": 0.7959003448486328,
232
+ "sampling/sampling_logp_difference/mean": 0.048079028725624084,
233
+ "step": 6,
234
+ "step_time": 37.11783460799961
235
+ },
236
+ {
237
+ "clip_ratio/high_max": 0.019634235184639692,
238
+ "clip_ratio/high_mean": 0.014030600897967815,
239
+ "clip_ratio/low_mean": 0.005204149056226015,
240
+ "clip_ratio/low_min": 0.002577319508418441,
241
+ "clip_ratio/region_mean": 0.019234750187024474,
242
+ "completions/clipped_ratio": 0.0,
243
+ "completions/max_length": 10.0,
244
+ "completions/max_terminated_length": 10.0,
245
+ "completions/mean_length": 2.282738208770752,
246
+ "completions/mean_terminated_length": 2.282738208770752,
247
+ "completions/min_length": 2.0,
248
+ "completions/min_terminated_length": 2.0,
249
+ "entropy": 0.6793178021907806,
250
+ "epoch": 1.75,
251
+ "frac_reward_zero_std": 0.5059524178504944,
252
+ "grad_norm": 2.815258741378784,
253
+ "learning_rate": 1.7058239999999999e-06,
254
+ "loss": 0.0239,
255
+ "num_tokens": 773929.0,
256
+ "reward": 0.4851190447807312,
257
+ "reward_std": 0.4990306794643402,
258
+ "rewards/env_game_reward/mean": 0.4851190447807312,
259
+ "rewards/env_game_reward/std": 0.4990306794643402,
260
+ "sampling/importance_sampling_ratio/max": 1.8610674142837524,
261
+ "sampling/importance_sampling_ratio/mean": 1.0055298805236816,
262
+ "sampling/importance_sampling_ratio/min": 0.0,
263
+ "sampling/sampling_logp_difference/max": 0.8122937679290771,
264
+ "sampling/sampling_logp_difference/mean": 0.07463809102773666,
265
+ "step": 7,
266
+ "step_time": 63.86528683999859
267
+ },
268
+ {
269
+ "clip_ratio/high_max": 0.01532895234413445,
270
+ "clip_ratio/high_mean": 0.008953135926276445,
271
+ "clip_ratio/low_mean": 0.009014535578899086,
272
+ "clip_ratio/low_min": 0.0024038462433964014,
273
+ "clip_ratio/region_mean": 0.017967671272344887,
274
+ "completions/clipped_ratio": 0.0,
275
+ "completions/max_length": 3.0,
276
+ "completions/max_terminated_length": 3.0,
277
+ "completions/mean_length": 2.2708334922790527,
278
+ "completions/mean_terminated_length": 2.2708334922790527,
279
+ "completions/min_length": 2.0,
280
+ "completions/min_terminated_length": 2.0,
281
+ "entropy": 0.6921011656522751,
282
+ "epoch": 2.0,
283
+ "frac_reward_zero_std": 0.4523809552192688,
284
+ "grad_norm": 2.390941619873047,
285
+ "learning_rate": 1.9901279999999997e-06,
286
+ "loss": 0.0071,
287
+ "num_tokens": 883556.0,
288
+ "reward": 0.5595238208770752,
289
+ "reward_std": 0.48962223529815674,
290
+ "rewards/env_game_reward/mean": 0.5595238208770752,
291
+ "rewards/env_game_reward/std": 0.48962223529815674,
292
+ "sampling/importance_sampling_ratio/max": 1.963092565536499,
293
+ "sampling/importance_sampling_ratio/mean": 0.9806411266326904,
294
+ "sampling/importance_sampling_ratio/min": 0.33748432993888855,
295
+ "sampling/sampling_logp_difference/max": 1.0179762840270996,
296
+ "sampling/sampling_logp_difference/mean": 0.07029423117637634,
297
+ "step": 8,
298
+ "step_time": 61.923666292001144
299
+ },
300
+ {
301
+ "epoch": 2.0,
302
+ "eval_clip_ratio/high_max": 0.0,
303
+ "eval_clip_ratio/high_mean": 0.0,
304
+ "eval_clip_ratio/low_mean": 0.0,
305
+ "eval_clip_ratio/low_min": 0.0,
306
+ "eval_clip_ratio/region_mean": 0.0,
307
+ "eval_completions/clipped_ratio": 0.0,
308
+ "eval_completions/max_length": 2.96,
309
+ "eval_completions/max_terminated_length": 2.96,
310
+ "eval_completions/mean_length": 2.25,
311
+ "eval_completions/mean_terminated_length": 2.25,
312
+ "eval_completions/min_length": 2.0,
313
+ "eval_completions/min_terminated_length": 2.0,
314
+ "eval_entropy": 0.663043782711029,
315
+ "eval_frac_reward_zero_std": 0.585,
316
+ "eval_loss": 0.014494094997644424,
317
+ "eval_num_tokens": 883556.0,
318
+ "eval_reward": 0.56,
319
+ "eval_reward_std": 0.458708074092865,
320
+ "eval_rewards/env_game_reward/mean": 0.56,
321
+ "eval_rewards/env_game_reward/std": 0.4587080860137939,
322
+ "eval_runtime": 84.5816,
323
+ "eval_samples_per_second": 2.365,
324
+ "eval_sampling/importance_sampling_ratio/max": 1.2596182644367218,
325
+ "eval_sampling/importance_sampling_ratio/mean": 0.9817599618434906,
326
+ "eval_sampling/importance_sampling_ratio/min": 0.7732881844043732,
327
+ "eval_sampling/sampling_logp_difference/max": 0.30535031914710997,
328
+ "eval_sampling/sampling_logp_difference/mean": 0.06819972261786461,
329
+ "eval_steps_per_second": 0.296,
330
+ "step": 8
331
+ }
332
+ ],
333
+ "logging_steps": 1.0,
334
+ "max_steps": 40,
335
+ "num_input_tokens_seen": 883556,
336
+ "num_train_epochs": 10,
337
+ "save_steps": 500,
338
+ "stateful_callbacks": {
339
+ "TrainerControl": {
340
+ "args": {
341
+ "should_epoch_stop": false,
342
+ "should_evaluate": false,
343
+ "should_log": false,
344
+ "should_save": true,
345
+ "should_training_stop": false
346
+ },
347
+ "attributes": {}
348
+ }
349
+ },
350
+ "total_flos": 0.0,
351
+ "train_batch_size": 42,
352
+ "trial_name": null,
353
+ "trial_params": null
354
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c032b79691ec0f0ef3021b1a710ed25323ffa7544442b5a3dae4d76703d8ce5d
3
+ size 7889