Carol0110 commited on
Commit
ff5eb27
1 Parent(s): d8f1430

Upload 13 files

Browse files
guardrank_lora/README.md ADDED
@@ -0,0 +1,206 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /mnt/cachenew/gutianle/modelscope/Llama-2-7b-ms
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- 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. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ 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).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ## Training procedure
201
+
202
+
203
+ ### Framework versions
204
+
205
+
206
+ - PEFT 0.6.2
guardrank_lora/adapter_config.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/mnt/cachenew/gutianle/modelscope/Llama-2-7b-ms",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 16,
12
+ "lora_dropout": 0.1,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 8,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "q_proj",
20
+ "o_proj",
21
+ "v_proj",
22
+ "k_proj"
23
+ ],
24
+ "task_type": "SEQ_CLS"
25
+ }
guardrank_lora/adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cecc9a384baf2b3b9a067c6665248508e958c9738b255c183a5ce0b710303c45
3
+ size 33712718
guardrank_lora/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<pad>": 32000
3
+ }
guardrank_lora/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c1b4295392cdb98a4360531b562f5f9e1c786673f46a214dcd94b42b97d85ba4
3
+ size 67455546
guardrank_lora/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:70de0cb45e748531ca4e97cd52bc06b38d076f30a6495dca9796b098072c48de
3
+ size 14244
guardrank_lora/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:641b0577c8df5dd91e5c9b25b70d6684b9fb3e8b805e34cc6f701af57a574234
3
+ size 1064
guardrank_lora/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": true,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
guardrank_lora/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
guardrank_lora/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
guardrank_lora/tokenizer_config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "__type": "AddedToken",
4
+ "content": "<s>",
5
+ "lstrip": false,
6
+ "normalized": true,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "clean_up_tokenization_spaces": false,
11
+ "eos_token": {
12
+ "__type": "AddedToken",
13
+ "content": "</s>",
14
+ "lstrip": false,
15
+ "normalized": true,
16
+ "rstrip": false,
17
+ "single_word": false
18
+ },
19
+ "legacy": false,
20
+ "model_max_length": 1000000000000000019884624838656,
21
+ "pad_token": null,
22
+ "sp_model_kwargs": {},
23
+ "tokenizer_class": "LlamaTokenizer",
24
+ "unk_token": {
25
+ "__type": "AddedToken",
26
+ "content": "<unk>",
27
+ "lstrip": false,
28
+ "normalized": true,
29
+ "rstrip": false,
30
+ "single_word": false
31
+ },
32
+ "use_default_system_prompt": true
33
+ }
guardrank_lora/trainer_state.json ADDED
@@ -0,0 +1,343 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.7517201834862385,
3
+ "best_model_checkpoint": "/mnt/cachenew/gutianle/llama2-scorer-non-existent/checkpoint-1800",
4
+ "epoch": 0.9174311926605505,
5
+ "eval_steps": 100,
6
+ "global_step": 1800,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.05,
13
+ "learning_rate": 0.0001,
14
+ "loss": 1.409,
15
+ "step": 100
16
+ },
17
+ {
18
+ "epoch": 0.05,
19
+ "eval_accuracy": 0.4294724770642202,
20
+ "eval_f1-score": 0.41676886432858656,
21
+ "eval_loss": 1.2865188121795654,
22
+ "eval_precision": 0.5191394843763429,
23
+ "eval_recall": 0.4294724770642202,
24
+ "eval_runtime": 100.35,
25
+ "eval_samples_per_second": 17.379,
26
+ "eval_steps_per_second": 2.172,
27
+ "step": 100
28
+ },
29
+ {
30
+ "epoch": 0.1,
31
+ "learning_rate": 0.0001,
32
+ "loss": 1.0433,
33
+ "step": 200
34
+ },
35
+ {
36
+ "epoch": 0.1,
37
+ "eval_accuracy": 0.6439220183486238,
38
+ "eval_f1-score": 0.6287928936906987,
39
+ "eval_loss": 0.9169857501983643,
40
+ "eval_precision": 0.6326166016462452,
41
+ "eval_recall": 0.6439220183486238,
42
+ "eval_runtime": 99.1386,
43
+ "eval_samples_per_second": 17.592,
44
+ "eval_steps_per_second": 2.199,
45
+ "step": 200
46
+ },
47
+ {
48
+ "epoch": 0.15,
49
+ "learning_rate": 0.0001,
50
+ "loss": 0.9457,
51
+ "step": 300
52
+ },
53
+ {
54
+ "epoch": 0.15,
55
+ "eval_accuracy": 0.573394495412844,
56
+ "eval_f1-score": 0.5780536942349181,
57
+ "eval_loss": 0.9270332455635071,
58
+ "eval_precision": 0.6119488919407539,
59
+ "eval_recall": 0.573394495412844,
60
+ "eval_runtime": 99.5145,
61
+ "eval_samples_per_second": 17.525,
62
+ "eval_steps_per_second": 2.191,
63
+ "step": 300
64
+ },
65
+ {
66
+ "epoch": 0.2,
67
+ "learning_rate": 0.0001,
68
+ "loss": 0.8176,
69
+ "step": 400
70
+ },
71
+ {
72
+ "epoch": 0.2,
73
+ "eval_accuracy": 0.6702981651376146,
74
+ "eval_f1-score": 0.6704055625650827,
75
+ "eval_loss": 0.8484154343605042,
76
+ "eval_precision": 0.6748752577010106,
77
+ "eval_recall": 0.6702981651376146,
78
+ "eval_runtime": 99.7876,
79
+ "eval_samples_per_second": 17.477,
80
+ "eval_steps_per_second": 2.185,
81
+ "step": 400
82
+ },
83
+ {
84
+ "epoch": 0.25,
85
+ "learning_rate": 0.0001,
86
+ "loss": 0.7769,
87
+ "step": 500
88
+ },
89
+ {
90
+ "epoch": 0.25,
91
+ "eval_accuracy": 0.6955275229357798,
92
+ "eval_f1-score": 0.6937246764104357,
93
+ "eval_loss": 0.8070082068443298,
94
+ "eval_precision": 0.6933530425142568,
95
+ "eval_recall": 0.6955275229357798,
96
+ "eval_runtime": 99.3769,
97
+ "eval_samples_per_second": 17.549,
98
+ "eval_steps_per_second": 2.194,
99
+ "step": 500
100
+ },
101
+ {
102
+ "epoch": 0.31,
103
+ "learning_rate": 0.0001,
104
+ "loss": 0.7069,
105
+ "step": 600
106
+ },
107
+ {
108
+ "epoch": 0.31,
109
+ "eval_accuracy": 0.6961009174311926,
110
+ "eval_f1-score": 0.6962474525389031,
111
+ "eval_loss": 0.8322665095329285,
112
+ "eval_precision": 0.7002298404175326,
113
+ "eval_recall": 0.6961009174311926,
114
+ "eval_runtime": 99.2464,
115
+ "eval_samples_per_second": 17.572,
116
+ "eval_steps_per_second": 2.197,
117
+ "step": 600
118
+ },
119
+ {
120
+ "epoch": 0.36,
121
+ "learning_rate": 0.0001,
122
+ "loss": 0.6742,
123
+ "step": 700
124
+ },
125
+ {
126
+ "epoch": 0.36,
127
+ "eval_accuracy": 0.7276376146788991,
128
+ "eval_f1-score": 0.7163514624677091,
129
+ "eval_loss": 0.7878208160400391,
130
+ "eval_precision": 0.731064800275646,
131
+ "eval_recall": 0.7276376146788991,
132
+ "eval_runtime": 99.1023,
133
+ "eval_samples_per_second": 17.598,
134
+ "eval_steps_per_second": 2.2,
135
+ "step": 700
136
+ },
137
+ {
138
+ "epoch": 0.41,
139
+ "learning_rate": 0.0001,
140
+ "loss": 0.7139,
141
+ "step": 800
142
+ },
143
+ {
144
+ "epoch": 0.41,
145
+ "eval_accuracy": 0.694954128440367,
146
+ "eval_f1-score": 0.7017678594633088,
147
+ "eval_loss": 0.7812691926956177,
148
+ "eval_precision": 0.7171557777434424,
149
+ "eval_recall": 0.694954128440367,
150
+ "eval_runtime": 99.2742,
151
+ "eval_samples_per_second": 17.568,
152
+ "eval_steps_per_second": 2.196,
153
+ "step": 800
154
+ },
155
+ {
156
+ "epoch": 0.46,
157
+ "learning_rate": 0.0001,
158
+ "loss": 0.7566,
159
+ "step": 900
160
+ },
161
+ {
162
+ "epoch": 0.46,
163
+ "eval_accuracy": 0.6909403669724771,
164
+ "eval_f1-score": 0.6922199349668261,
165
+ "eval_loss": 0.7475219368934631,
166
+ "eval_precision": 0.7040747986976179,
167
+ "eval_recall": 0.6909403669724771,
168
+ "eval_runtime": 99.2593,
169
+ "eval_samples_per_second": 17.57,
170
+ "eval_steps_per_second": 2.196,
171
+ "step": 900
172
+ },
173
+ {
174
+ "epoch": 0.51,
175
+ "learning_rate": 0.0001,
176
+ "loss": 0.6692,
177
+ "step": 1000
178
+ },
179
+ {
180
+ "epoch": 0.51,
181
+ "eval_accuracy": 0.6857798165137615,
182
+ "eval_f1-score": 0.6973150689879362,
183
+ "eval_loss": 0.7810325026512146,
184
+ "eval_precision": 0.7120290886583457,
185
+ "eval_recall": 0.6857798165137615,
186
+ "eval_runtime": 99.239,
187
+ "eval_samples_per_second": 17.574,
188
+ "eval_steps_per_second": 2.197,
189
+ "step": 1000
190
+ },
191
+ {
192
+ "epoch": 0.56,
193
+ "learning_rate": 0.0001,
194
+ "loss": 0.6733,
195
+ "step": 1100
196
+ },
197
+ {
198
+ "epoch": 0.56,
199
+ "eval_accuracy": 0.7368119266055045,
200
+ "eval_f1-score": 0.7271862000397501,
201
+ "eval_loss": 0.7271122336387634,
202
+ "eval_precision": 0.74773502586483,
203
+ "eval_recall": 0.7368119266055045,
204
+ "eval_runtime": 99.0466,
205
+ "eval_samples_per_second": 17.608,
206
+ "eval_steps_per_second": 2.201,
207
+ "step": 1100
208
+ },
209
+ {
210
+ "epoch": 0.61,
211
+ "learning_rate": 0.0001,
212
+ "loss": 0.6356,
213
+ "step": 1200
214
+ },
215
+ {
216
+ "epoch": 0.61,
217
+ "eval_accuracy": 0.7253440366972477,
218
+ "eval_f1-score": 0.7249868939903279,
219
+ "eval_loss": 0.7682604193687439,
220
+ "eval_precision": 0.7249192202979644,
221
+ "eval_recall": 0.7253440366972477,
222
+ "eval_runtime": 99.36,
223
+ "eval_samples_per_second": 17.552,
224
+ "eval_steps_per_second": 2.194,
225
+ "step": 1200
226
+ },
227
+ {
228
+ "epoch": 0.66,
229
+ "learning_rate": 0.0001,
230
+ "loss": 0.6112,
231
+ "step": 1300
232
+ },
233
+ {
234
+ "epoch": 0.66,
235
+ "eval_accuracy": 0.7264908256880734,
236
+ "eval_f1-score": 0.7199307263891085,
237
+ "eval_loss": 0.8078410029411316,
238
+ "eval_precision": 0.7206056594932215,
239
+ "eval_recall": 0.7264908256880734,
240
+ "eval_runtime": 99.258,
241
+ "eval_samples_per_second": 17.57,
242
+ "eval_steps_per_second": 2.196,
243
+ "step": 1300
244
+ },
245
+ {
246
+ "epoch": 0.71,
247
+ "learning_rate": 0.0001,
248
+ "loss": 0.646,
249
+ "step": 1400
250
+ },
251
+ {
252
+ "epoch": 0.71,
253
+ "eval_accuracy": 0.7431192660550459,
254
+ "eval_f1-score": 0.7350696097040301,
255
+ "eval_loss": 0.7144489288330078,
256
+ "eval_precision": 0.7421391963845961,
257
+ "eval_recall": 0.7431192660550459,
258
+ "eval_runtime": 99.3431,
259
+ "eval_samples_per_second": 17.555,
260
+ "eval_steps_per_second": 2.194,
261
+ "step": 1400
262
+ },
263
+ {
264
+ "epoch": 0.76,
265
+ "learning_rate": 0.0001,
266
+ "loss": 0.6052,
267
+ "step": 1500
268
+ },
269
+ {
270
+ "epoch": 0.76,
271
+ "eval_accuracy": 0.7471330275229358,
272
+ "eval_f1-score": 0.7394703056430186,
273
+ "eval_loss": 0.679287850856781,
274
+ "eval_precision": 0.7525699542508473,
275
+ "eval_recall": 0.7471330275229358,
276
+ "eval_runtime": 99.4231,
277
+ "eval_samples_per_second": 17.541,
278
+ "eval_steps_per_second": 2.193,
279
+ "step": 1500
280
+ },
281
+ {
282
+ "epoch": 0.82,
283
+ "learning_rate": 0.0001,
284
+ "loss": 0.6004,
285
+ "step": 1600
286
+ },
287
+ {
288
+ "epoch": 0.82,
289
+ "eval_accuracy": 0.75,
290
+ "eval_f1-score": 0.7503577703532133,
291
+ "eval_loss": 0.7611460089683533,
292
+ "eval_precision": 0.7582961750700967,
293
+ "eval_recall": 0.75,
294
+ "eval_runtime": 99.3947,
295
+ "eval_samples_per_second": 17.546,
296
+ "eval_steps_per_second": 2.193,
297
+ "step": 1600
298
+ },
299
+ {
300
+ "epoch": 0.87,
301
+ "learning_rate": 0.0001,
302
+ "loss": 0.6041,
303
+ "step": 1700
304
+ },
305
+ {
306
+ "epoch": 0.87,
307
+ "eval_accuracy": 0.7563073394495413,
308
+ "eval_f1-score": 0.7497128952328905,
309
+ "eval_loss": 0.7003496289253235,
310
+ "eval_precision": 0.7580686951357652,
311
+ "eval_recall": 0.7563073394495413,
312
+ "eval_runtime": 99.3241,
313
+ "eval_samples_per_second": 17.559,
314
+ "eval_steps_per_second": 2.195,
315
+ "step": 1700
316
+ },
317
+ {
318
+ "epoch": 0.92,
319
+ "learning_rate": 0.0001,
320
+ "loss": 0.5445,
321
+ "step": 1800
322
+ },
323
+ {
324
+ "epoch": 0.92,
325
+ "eval_accuracy": 0.7517201834862385,
326
+ "eval_f1-score": 0.7465676797118755,
327
+ "eval_loss": 0.6659787893295288,
328
+ "eval_precision": 0.7528237883767219,
329
+ "eval_recall": 0.7517201834862385,
330
+ "eval_runtime": 99.3316,
331
+ "eval_samples_per_second": 17.557,
332
+ "eval_steps_per_second": 2.195,
333
+ "step": 1800
334
+ }
335
+ ],
336
+ "logging_steps": 100,
337
+ "max_steps": 5886,
338
+ "num_train_epochs": 3,
339
+ "save_steps": 200,
340
+ "total_flos": 2.868620669485056e+17,
341
+ "trial_name": null,
342
+ "trial_params": null
343
+ }
guardrank_lora/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:823820e217deb656ea241281687228f7d92e30b4248ef149e21b0e6464e80ccc
3
+ size 4536