CSMaya commited on
Commit
0b44bd4
·
verified ·
1 Parent(s): 984655b

Upload folder using huggingface_hub

Browse files
Files changed (49) hide show
  1. justification-only-lora/README.md +62 -0
  2. justification-only-lora/adapter_config.json +46 -0
  3. justification-only-lora/adapter_model.safetensors +3 -0
  4. justification-only-lora/chat_template.jinja +1 -0
  5. justification-only-lora/checkpoint-1042/README.md +209 -0
  6. justification-only-lora/checkpoint-1042/adapter_config.json +46 -0
  7. justification-only-lora/checkpoint-1042/adapter_model.safetensors +3 -0
  8. justification-only-lora/checkpoint-1042/chat_template.jinja +1 -0
  9. justification-only-lora/checkpoint-1042/optimizer.pt +3 -0
  10. justification-only-lora/checkpoint-1042/rng_state.pth +3 -0
  11. justification-only-lora/checkpoint-1042/scheduler.pt +3 -0
  12. justification-only-lora/checkpoint-1042/special_tokens_map.json +24 -0
  13. justification-only-lora/checkpoint-1042/tokenizer.json +0 -0
  14. justification-only-lora/checkpoint-1042/tokenizer.model +3 -0
  15. justification-only-lora/checkpoint-1042/tokenizer_config.json +43 -0
  16. justification-only-lora/checkpoint-1042/trainer_state.json +1074 -0
  17. justification-only-lora/checkpoint-1042/training_args.bin +3 -0
  18. justification-only-lora/checkpoint-1563/README.md +209 -0
  19. justification-only-lora/checkpoint-1563/adapter_config.json +46 -0
  20. justification-only-lora/checkpoint-1563/adapter_model.safetensors +3 -0
  21. justification-only-lora/checkpoint-1563/chat_template.jinja +1 -0
  22. justification-only-lora/checkpoint-1563/optimizer.pt +3 -0
  23. justification-only-lora/checkpoint-1563/rng_state.pth +3 -0
  24. justification-only-lora/checkpoint-1563/scheduler.pt +3 -0
  25. justification-only-lora/checkpoint-1563/special_tokens_map.json +24 -0
  26. justification-only-lora/checkpoint-1563/tokenizer.json +0 -0
  27. justification-only-lora/checkpoint-1563/tokenizer.model +3 -0
  28. justification-only-lora/checkpoint-1563/tokenizer_config.json +43 -0
  29. justification-only-lora/checkpoint-1563/trainer_state.json +1594 -0
  30. justification-only-lora/checkpoint-1563/training_args.bin +3 -0
  31. justification-only-lora/checkpoint-521/README.md +209 -0
  32. justification-only-lora/checkpoint-521/adapter_config.json +46 -0
  33. justification-only-lora/checkpoint-521/adapter_model.safetensors +3 -0
  34. justification-only-lora/checkpoint-521/chat_template.jinja +1 -0
  35. justification-only-lora/checkpoint-521/optimizer.pt +3 -0
  36. justification-only-lora/checkpoint-521/rng_state.pth +3 -0
  37. justification-only-lora/checkpoint-521/scheduler.pt +3 -0
  38. justification-only-lora/checkpoint-521/special_tokens_map.json +24 -0
  39. justification-only-lora/checkpoint-521/tokenizer.json +0 -0
  40. justification-only-lora/checkpoint-521/tokenizer.model +3 -0
  41. justification-only-lora/checkpoint-521/tokenizer_config.json +43 -0
  42. justification-only-lora/checkpoint-521/trainer_state.json +554 -0
  43. justification-only-lora/checkpoint-521/training_args.bin +3 -0
  44. justification-only-lora/run_config.json +13 -0
  45. justification-only-lora/special_tokens_map.json +24 -0
  46. justification-only-lora/tokenizer.json +0 -0
  47. justification-only-lora/tokenizer.model +3 -0
  48. justification-only-lora/tokenizer_config.json +43 -0
  49. justification-only-lora/training_args.bin +3 -0
justification-only-lora/README.md ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-2-7b-chat-hf
3
+ library_name: peft
4
+ model_name: llama2-7b-chat-er-justification-only-lora
5
+ tags:
6
+ - base_model:adapter:meta-llama/Llama-2-7b-chat-hf
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ licence: license
12
+ pipeline_tag: text-generation
13
+ ---
14
+
15
+ # Model Card for llama2-7b-chat-er-justification-only-lora
16
+
17
+ This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf).
18
+ It has been trained using [TRL](https://github.com/huggingface/trl).
19
+
20
+ ## Quick start
21
+
22
+ ```python
23
+ from transformers import pipeline
24
+
25
+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
26
+ generator = pipeline("text-generation", model="None", device="cuda")
27
+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
28
+ print(output["generated_text"])
29
+ ```
30
+
31
+ ## Training procedure
32
+
33
+
34
+
35
+
36
+
37
+ This model was trained with SFT.
38
+
39
+ ### Framework versions
40
+
41
+ - PEFT 0.18.1
42
+ - TRL: 1.0.0
43
+ - Transformers: 4.57.6
44
+ - Pytorch: 2.7.0+cu126
45
+ - Datasets: 4.8.4
46
+ - Tokenizers: 0.22.2
47
+
48
+ ## Citations
49
+
50
+
51
+
52
+ Cite TRL as:
53
+
54
+ ```bibtex
55
+ @software{vonwerra2020trl,
56
+ title = {{TRL: Transformers Reinforcement Learning}},
57
+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
58
+ license = {Apache-2.0},
59
+ url = {https://github.com/huggingface/trl},
60
+ year = {2020}
61
+ }
62
+ ```
justification-only-lora/adapter_config.json ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
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": 128,
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": 64,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "q_proj",
33
+ "k_proj",
34
+ "v_proj",
35
+ "up_proj",
36
+ "o_proj",
37
+ "down_proj",
38
+ "gate_proj"
39
+ ],
40
+ "target_parameters": null,
41
+ "task_type": "CAUSAL_LM",
42
+ "trainable_token_indices": null,
43
+ "use_dora": false,
44
+ "use_qalora": false,
45
+ "use_rslora": false
46
+ }
justification-only-lora/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1ab80ac53fdda79ab48e10a93f9604688ea4f39ea619486708628153a6303636
3
+ size 639691872
justification-only-lora/chat_template.jinja ADDED
@@ -0,0 +1 @@
 
 
1
+ {% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}
justification-only-lora/checkpoint-1042/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-2-7b-chat-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:meta-llama/Llama-2-7b-chat-hf
7
+ - lora
8
+ - sft
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
justification-only-lora/checkpoint-1042/adapter_config.json ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
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": 128,
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": 64,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "q_proj",
33
+ "k_proj",
34
+ "v_proj",
35
+ "up_proj",
36
+ "o_proj",
37
+ "down_proj",
38
+ "gate_proj"
39
+ ],
40
+ "target_parameters": null,
41
+ "task_type": "CAUSAL_LM",
42
+ "trainable_token_indices": null,
43
+ "use_dora": false,
44
+ "use_qalora": false,
45
+ "use_rslora": false
46
+ }
justification-only-lora/checkpoint-1042/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ea05576374021ecffb9ab85f97fdb00304f3766944b11387e672d7e9fed336d2
3
+ size 639691872
justification-only-lora/checkpoint-1042/chat_template.jinja ADDED
@@ -0,0 +1 @@
 
 
1
+ {% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}
justification-only-lora/checkpoint-1042/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:17a15f05aab3ba30d00a3d11fb5f2ae193cab78c22718ad8b45ff4d8d5257dc8
3
+ size 1279641507
justification-only-lora/checkpoint-1042/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:660c81e5597540b0e82a95a8ae972e90d26f2c39279b57eb6e818bc7333e8c1b
3
+ size 14645
justification-only-lora/checkpoint-1042/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5259f0e9223403187bb50bf58f05f22c78e33253af5e6a73ab30ea287bcd49f8
3
+ size 1465
justification-only-lora/checkpoint-1042/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
justification-only-lora/checkpoint-1042/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
justification-only-lora/checkpoint-1042/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
justification-only-lora/checkpoint-1042/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": null,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": false,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false
43
+ }
justification-only-lora/checkpoint-1042/trainer_state.json ADDED
@@ -0,0 +1,1074 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": 1042,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.5444401994347572,
14
+ "epoch": 0.019193857965451054,
15
+ "grad_norm": 5.821522235870361,
16
+ "learning_rate": 1.9148936170212765e-07,
17
+ "loss": 4.1401,
18
+ "mean_token_accuracy": 0.4060008004307747,
19
+ "num_tokens": 4245.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 1.5042417280375957,
24
+ "epoch": 0.03838771593090211,
25
+ "grad_norm": 5.973490238189697,
26
+ "learning_rate": 4.0425531914893614e-07,
27
+ "loss": 4.0713,
28
+ "mean_token_accuracy": 0.4032037228345871,
29
+ "num_tokens": 8699.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 1.5192734643816947,
34
+ "epoch": 0.05758157389635317,
35
+ "grad_norm": 5.376368999481201,
36
+ "learning_rate": 6.170212765957446e-07,
37
+ "loss": 3.9752,
38
+ "mean_token_accuracy": 0.396929800696671,
39
+ "num_tokens": 13344.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 1.5850717440247535,
44
+ "epoch": 0.07677543186180422,
45
+ "grad_norm": 4.978009223937988,
46
+ "learning_rate": 8.297872340425532e-07,
47
+ "loss": 4.0101,
48
+ "mean_token_accuracy": 0.398511266708374,
49
+ "num_tokens": 17548.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 1.609639537334442,
54
+ "epoch": 0.09596928982725528,
55
+ "grad_norm": 5.168197154998779,
56
+ "learning_rate": 9.986807387862796e-07,
57
+ "loss": 4.0455,
58
+ "mean_token_accuracy": 0.39038523491472005,
59
+ "num_tokens": 21726.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 1.6230455122888088,
64
+ "epoch": 0.11516314779270634,
65
+ "grad_norm": 4.924302577972412,
66
+ "learning_rate": 9.92084432717678e-07,
67
+ "loss": 3.805,
68
+ "mean_token_accuracy": 0.41029399298131464,
69
+ "num_tokens": 26305.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 1.6385258689522744,
74
+ "epoch": 0.1343570057581574,
75
+ "grad_norm": 5.023738861083984,
76
+ "learning_rate": 9.854881266490765e-07,
77
+ "loss": 3.6963,
78
+ "mean_token_accuracy": 0.4034191995859146,
79
+ "num_tokens": 30867.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 1.6791253253817557,
84
+ "epoch": 0.15355086372360843,
85
+ "grad_norm": 4.995085716247559,
86
+ "learning_rate": 9.788918205804749e-07,
87
+ "loss": 3.5687,
88
+ "mean_token_accuracy": 0.41049087755382063,
89
+ "num_tokens": 35488.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 1.7368177756667138,
94
+ "epoch": 0.1727447216890595,
95
+ "grad_norm": 5.233994007110596,
96
+ "learning_rate": 9.722955145118733e-07,
97
+ "loss": 3.502,
98
+ "mean_token_accuracy": 0.41353076659142973,
99
+ "num_tokens": 39905.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 1.7768422558903694,
104
+ "epoch": 0.19193857965451055,
105
+ "grad_norm": 4.299875259399414,
106
+ "learning_rate": 9.656992084432716e-07,
107
+ "loss": 3.4098,
108
+ "mean_token_accuracy": 0.4197281800210476,
109
+ "num_tokens": 44208.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 1.8558007434010506,
114
+ "epoch": 0.21113243761996162,
115
+ "grad_norm": 4.665222644805908,
116
+ "learning_rate": 9.591029023746702e-07,
117
+ "loss": 3.2665,
118
+ "mean_token_accuracy": 0.42318747080862523,
119
+ "num_tokens": 48508.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 1.8271729901432991,
124
+ "epoch": 0.23032629558541268,
125
+ "grad_norm": 3.741534948348999,
126
+ "learning_rate": 9.525065963060686e-07,
127
+ "loss": 3.0302,
128
+ "mean_token_accuracy": 0.4432856226339936,
129
+ "num_tokens": 53006.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 1.855116668343544,
134
+ "epoch": 0.2495201535508637,
135
+ "grad_norm": 3.7163283824920654,
136
+ "learning_rate": 9.459102902374669e-07,
137
+ "loss": 2.9221,
138
+ "mean_token_accuracy": 0.45197133012115953,
139
+ "num_tokens": 57517.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 1.8998430132865907,
144
+ "epoch": 0.2687140115163148,
145
+ "grad_norm": 3.359804153442383,
146
+ "learning_rate": 9.393139841688654e-07,
147
+ "loss": 2.862,
148
+ "mean_token_accuracy": 0.4820567347109318,
149
+ "num_tokens": 61859.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 1.8810108318924903,
154
+ "epoch": 0.28790786948176583,
155
+ "grad_norm": 3.24143648147583,
156
+ "learning_rate": 9.327176781002638e-07,
157
+ "loss": 2.6863,
158
+ "mean_token_accuracy": 0.4882553808391094,
159
+ "num_tokens": 66294.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 1.8664621368050576,
164
+ "epoch": 0.30710172744721687,
165
+ "grad_norm": 3.21515154838562,
166
+ "learning_rate": 9.261213720316622e-07,
167
+ "loss": 2.5571,
168
+ "mean_token_accuracy": 0.4904331646859646,
169
+ "num_tokens": 70881.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 1.9047470435500145,
174
+ "epoch": 0.32629558541266795,
175
+ "grad_norm": 2.9383370876312256,
176
+ "learning_rate": 9.195250659630607e-07,
177
+ "loss": 2.4253,
178
+ "mean_token_accuracy": 0.5186557050794363,
179
+ "num_tokens": 75343.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 1.8957982853055,
184
+ "epoch": 0.345489443378119,
185
+ "grad_norm": 2.855672836303711,
186
+ "learning_rate": 9.129287598944591e-07,
187
+ "loss": 2.3765,
188
+ "mean_token_accuracy": 0.5165872510522604,
189
+ "num_tokens": 79813.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 1.8749225288629532,
194
+ "epoch": 0.3646833013435701,
195
+ "grad_norm": 2.4022603034973145,
196
+ "learning_rate": 9.063324538258574e-07,
197
+ "loss": 2.262,
198
+ "mean_token_accuracy": 0.5304524928331376,
199
+ "num_tokens": 84432.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 1.859298901259899,
204
+ "epoch": 0.3838771593090211,
205
+ "grad_norm": 2.477881908416748,
206
+ "learning_rate": 8.997361477572559e-07,
207
+ "loss": 2.1756,
208
+ "mean_token_accuracy": 0.5431556064635515,
209
+ "num_tokens": 88923.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 1.8629574179649353,
214
+ "epoch": 0.40307101727447214,
215
+ "grad_norm": 2.1476128101348877,
216
+ "learning_rate": 8.931398416886543e-07,
217
+ "loss": 2.1339,
218
+ "mean_token_accuracy": 0.5666973438113928,
219
+ "num_tokens": 93328.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 1.8807074934244157,
224
+ "epoch": 0.42226487523992323,
225
+ "grad_norm": 2.3548238277435303,
226
+ "learning_rate": 8.865435356200526e-07,
227
+ "loss": 2.0982,
228
+ "mean_token_accuracy": 0.5757683675736189,
229
+ "num_tokens": 97899.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 1.9242157697677613,
234
+ "epoch": 0.44145873320537427,
235
+ "grad_norm": 2.224064588546753,
236
+ "learning_rate": 8.799472295514512e-07,
237
+ "loss": 2.0095,
238
+ "mean_token_accuracy": 0.5813840452581645,
239
+ "num_tokens": 102067.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 1.8383784875273705,
244
+ "epoch": 0.46065259117082535,
245
+ "grad_norm": 2.35628604888916,
246
+ "learning_rate": 8.733509234828496e-07,
247
+ "loss": 2.0116,
248
+ "mean_token_accuracy": 0.582221444323659,
249
+ "num_tokens": 106474.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 1.8541715443134308,
254
+ "epoch": 0.4798464491362764,
255
+ "grad_norm": 2.1513049602508545,
256
+ "learning_rate": 8.667546174142479e-07,
257
+ "loss": 1.9723,
258
+ "mean_token_accuracy": 0.591744914278388,
259
+ "num_tokens": 110847.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 1.8240503028035164,
264
+ "epoch": 0.4990403071017274,
265
+ "grad_norm": 1.9908933639526367,
266
+ "learning_rate": 8.601583113456464e-07,
267
+ "loss": 1.9192,
268
+ "mean_token_accuracy": 0.583719938248396,
269
+ "num_tokens": 115237.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 1.8065304696559905,
274
+ "epoch": 0.5182341650671785,
275
+ "grad_norm": 2.1833651065826416,
276
+ "learning_rate": 8.535620052770448e-07,
277
+ "loss": 1.8791,
278
+ "mean_token_accuracy": 0.5988160844892263,
279
+ "num_tokens": 119549.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 1.7882312104105949,
284
+ "epoch": 0.5374280230326296,
285
+ "grad_norm": 2.280733823776245,
286
+ "learning_rate": 8.469656992084431e-07,
287
+ "loss": 1.899,
288
+ "mean_token_accuracy": 0.5769031669944524,
289
+ "num_tokens": 123989.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 1.7919606953859328,
294
+ "epoch": 0.5566218809980806,
295
+ "grad_norm": 2.1053104400634766,
296
+ "learning_rate": 8.403693931398417e-07,
297
+ "loss": 1.833,
298
+ "mean_token_accuracy": 0.5953757733106613,
299
+ "num_tokens": 128278.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 1.8032251179218293,
304
+ "epoch": 0.5758157389635317,
305
+ "grad_norm": 2.0865530967712402,
306
+ "learning_rate": 8.337730870712401e-07,
307
+ "loss": 1.8991,
308
+ "mean_token_accuracy": 0.5826169475913048,
309
+ "num_tokens": 133078.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 1.7583968698978425,
314
+ "epoch": 0.5950095969289827,
315
+ "grad_norm": 1.7579165697097778,
316
+ "learning_rate": 8.271767810026385e-07,
317
+ "loss": 1.7885,
318
+ "mean_token_accuracy": 0.6143867563456297,
319
+ "num_tokens": 137541.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 1.7979290679097175,
324
+ "epoch": 0.6142034548944337,
325
+ "grad_norm": 1.8130688667297363,
326
+ "learning_rate": 8.205804749340369e-07,
327
+ "loss": 1.8252,
328
+ "mean_token_accuracy": 0.6005033150315284,
329
+ "num_tokens": 141810.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 1.7790041908621788,
334
+ "epoch": 0.6333973128598849,
335
+ "grad_norm": 1.9245020151138306,
336
+ "learning_rate": 8.139841688654353e-07,
337
+ "loss": 1.7798,
338
+ "mean_token_accuracy": 0.613793533295393,
339
+ "num_tokens": 146112.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 1.7689658552408218,
344
+ "epoch": 0.6525911708253359,
345
+ "grad_norm": 2.208102226257324,
346
+ "learning_rate": 8.073878627968337e-07,
347
+ "loss": 1.7584,
348
+ "mean_token_accuracy": 0.5983480997383595,
349
+ "num_tokens": 150609.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 1.7603006795048715,
354
+ "epoch": 0.6717850287907869,
355
+ "grad_norm": 1.8552649021148682,
356
+ "learning_rate": 8.007915567282322e-07,
357
+ "loss": 1.7016,
358
+ "mean_token_accuracy": 0.6168740216642619,
359
+ "num_tokens": 155088.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 1.741025310754776,
364
+ "epoch": 0.690978886756238,
365
+ "grad_norm": 1.9795598983764648,
366
+ "learning_rate": 7.941952506596306e-07,
367
+ "loss": 1.7031,
368
+ "mean_token_accuracy": 0.6189993746578694,
369
+ "num_tokens": 159495.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 1.763644915819168,
374
+ "epoch": 0.710172744721689,
375
+ "grad_norm": 2.2528767585754395,
376
+ "learning_rate": 7.87598944591029e-07,
377
+ "loss": 1.6961,
378
+ "mean_token_accuracy": 0.6185917239636183,
379
+ "num_tokens": 163793.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 1.739506982266903,
384
+ "epoch": 0.7293666026871402,
385
+ "grad_norm": 1.9315766096115112,
386
+ "learning_rate": 7.810026385224274e-07,
387
+ "loss": 1.6339,
388
+ "mean_token_accuracy": 0.6323129627853632,
389
+ "num_tokens": 168268.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 1.7659575924277306,
394
+ "epoch": 0.7485604606525912,
395
+ "grad_norm": 1.8060170412063599,
396
+ "learning_rate": 7.744063324538258e-07,
397
+ "loss": 1.6461,
398
+ "mean_token_accuracy": 0.6334325969219208,
399
+ "num_tokens": 172612.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 1.7049371361732484,
404
+ "epoch": 0.7677543186180422,
405
+ "grad_norm": 1.7351154088974,
406
+ "learning_rate": 7.678100263852242e-07,
407
+ "loss": 1.5584,
408
+ "mean_token_accuracy": 0.64255366101861,
409
+ "num_tokens": 176987.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 1.6969178169965744,
414
+ "epoch": 0.7869481765834933,
415
+ "grad_norm": 1.5524696111679077,
416
+ "learning_rate": 7.612137203166226e-07,
417
+ "loss": 1.6435,
418
+ "mean_token_accuracy": 0.632745499163866,
419
+ "num_tokens": 181538.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 1.6801453217864037,
424
+ "epoch": 0.8061420345489443,
425
+ "grad_norm": 1.667938470840454,
426
+ "learning_rate": 7.546174142480211e-07,
427
+ "loss": 1.5851,
428
+ "mean_token_accuracy": 0.6391880080103874,
429
+ "num_tokens": 185819.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 1.6663354828953743,
434
+ "epoch": 0.8253358925143954,
435
+ "grad_norm": 1.5086743831634521,
436
+ "learning_rate": 7.480211081794196e-07,
437
+ "loss": 1.5759,
438
+ "mean_token_accuracy": 0.6453739482909441,
439
+ "num_tokens": 190254.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 1.6495836034417153,
444
+ "epoch": 0.8445297504798465,
445
+ "grad_norm": 1.7330267429351807,
446
+ "learning_rate": 7.414248021108179e-07,
447
+ "loss": 1.5403,
448
+ "mean_token_accuracy": 0.6486042737960815,
449
+ "num_tokens": 194643.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 1.6953262895345689,
454
+ "epoch": 0.8637236084452975,
455
+ "grad_norm": 1.465407133102417,
456
+ "learning_rate": 7.348284960422163e-07,
457
+ "loss": 1.5757,
458
+ "mean_token_accuracy": 0.6440861701965332,
459
+ "num_tokens": 198983.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 1.6009652018547058,
464
+ "epoch": 0.8829174664107485,
465
+ "grad_norm": 1.484931230545044,
466
+ "learning_rate": 7.282321899736148e-07,
467
+ "loss": 1.4547,
468
+ "mean_token_accuracy": 0.6605511672794819,
469
+ "num_tokens": 203270.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 1.6046269670128823,
474
+ "epoch": 0.9021113243761996,
475
+ "grad_norm": 1.4576069116592407,
476
+ "learning_rate": 7.216358839050131e-07,
477
+ "loss": 1.5508,
478
+ "mean_token_accuracy": 0.6439322311431169,
479
+ "num_tokens": 207696.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 1.6068053118884564,
484
+ "epoch": 0.9213051823416507,
485
+ "grad_norm": 1.7096375226974487,
486
+ "learning_rate": 7.150395778364116e-07,
487
+ "loss": 1.5665,
488
+ "mean_token_accuracy": 0.6389439355581998,
489
+ "num_tokens": 212574.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 1.58553556650877,
494
+ "epoch": 0.9404990403071017,
495
+ "grad_norm": 1.8892183303833008,
496
+ "learning_rate": 7.084432717678101e-07,
497
+ "loss": 1.5476,
498
+ "mean_token_accuracy": 0.6533854089677333,
499
+ "num_tokens": 217308.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 1.6013462141156196,
504
+ "epoch": 0.9596928982725528,
505
+ "grad_norm": 1.3890715837478638,
506
+ "learning_rate": 7.018469656992084e-07,
507
+ "loss": 1.5067,
508
+ "mean_token_accuracy": 0.6439886368811131,
509
+ "num_tokens": 221638.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 1.5622883230447768,
514
+ "epoch": 0.9788867562380038,
515
+ "grad_norm": 1.4576449394226074,
516
+ "learning_rate": 6.952506596306068e-07,
517
+ "loss": 1.5282,
518
+ "mean_token_accuracy": 0.6542089767754078,
519
+ "num_tokens": 226264.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 1.5611482337117195,
524
+ "epoch": 0.9980806142034548,
525
+ "grad_norm": 1.3677759170532227,
526
+ "learning_rate": 6.886543535620053e-07,
527
+ "loss": 1.4478,
528
+ "mean_token_accuracy": 0.6510695222765207,
529
+ "num_tokens": 230675.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 1.5630412474274635,
534
+ "epoch": 1.017274472168906,
535
+ "grad_norm": 1.451343297958374,
536
+ "learning_rate": 6.820580474934036e-07,
537
+ "loss": 1.5144,
538
+ "mean_token_accuracy": 0.6554066635668278,
539
+ "num_tokens": 235290.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 1.5062206633388997,
544
+ "epoch": 1.036468330134357,
545
+ "grad_norm": 1.4385675191879272,
546
+ "learning_rate": 6.75461741424802e-07,
547
+ "loss": 1.459,
548
+ "mean_token_accuracy": 0.6650427110493183,
549
+ "num_tokens": 239682.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 1.5518377706408502,
554
+ "epoch": 1.055662188099808,
555
+ "grad_norm": 1.3765565156936646,
556
+ "learning_rate": 6.688654353562006e-07,
557
+ "loss": 1.5403,
558
+ "mean_token_accuracy": 0.6449352588504553,
559
+ "num_tokens": 244138.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 1.5200361490249634,
564
+ "epoch": 1.0748560460652592,
565
+ "grad_norm": 1.356392741203308,
566
+ "learning_rate": 6.62269129287599e-07,
567
+ "loss": 1.4413,
568
+ "mean_token_accuracy": 0.6655519589781761,
569
+ "num_tokens": 248375.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 1.517387817800045,
574
+ "epoch": 1.0940499040307101,
575
+ "grad_norm": 1.2830088138580322,
576
+ "learning_rate": 6.556728232189973e-07,
577
+ "loss": 1.4174,
578
+ "mean_token_accuracy": 0.658090665563941,
579
+ "num_tokens": 252941.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 1.4819800563156604,
584
+ "epoch": 1.1132437619961613,
585
+ "grad_norm": 1.4165180921554565,
586
+ "learning_rate": 6.490765171503958e-07,
587
+ "loss": 1.4804,
588
+ "mean_token_accuracy": 0.6585468038916588,
589
+ "num_tokens": 257486.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 1.5246448263525962,
594
+ "epoch": 1.1324376199616122,
595
+ "grad_norm": 1.3312668800354004,
596
+ "learning_rate": 6.424802110817942e-07,
597
+ "loss": 1.473,
598
+ "mean_token_accuracy": 0.652620742097497,
599
+ "num_tokens": 261978.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 1.489580862224102,
604
+ "epoch": 1.1516314779270633,
605
+ "grad_norm": 1.2045397758483887,
606
+ "learning_rate": 6.358839050131925e-07,
607
+ "loss": 1.3997,
608
+ "mean_token_accuracy": 0.6628001451492309,
609
+ "num_tokens": 266337.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 1.49830242395401,
614
+ "epoch": 1.1708253358925145,
615
+ "grad_norm": 1.4452189207077026,
616
+ "learning_rate": 6.292875989445911e-07,
617
+ "loss": 1.4246,
618
+ "mean_token_accuracy": 0.6613333437591791,
619
+ "num_tokens": 270625.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 1.477701984345913,
624
+ "epoch": 1.1900191938579654,
625
+ "grad_norm": 1.4515446424484253,
626
+ "learning_rate": 6.226912928759895e-07,
627
+ "loss": 1.4386,
628
+ "mean_token_accuracy": 0.666374447196722,
629
+ "num_tokens": 274970.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 1.4627806089818478,
634
+ "epoch": 1.2092130518234165,
635
+ "grad_norm": 1.2604293823242188,
636
+ "learning_rate": 6.160949868073878e-07,
637
+ "loss": 1.4076,
638
+ "mean_token_accuracy": 0.6598449043929577,
639
+ "num_tokens": 279480.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 1.435338243842125,
644
+ "epoch": 1.2284069097888675,
645
+ "grad_norm": 1.2244068384170532,
646
+ "learning_rate": 6.094986807387863e-07,
647
+ "loss": 1.3863,
648
+ "mean_token_accuracy": 0.66046132594347,
649
+ "num_tokens": 283918.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 1.459252581000328,
654
+ "epoch": 1.2476007677543186,
655
+ "grad_norm": 1.3843801021575928,
656
+ "learning_rate": 6.029023746701847e-07,
657
+ "loss": 1.4447,
658
+ "mean_token_accuracy": 0.653592013567686,
659
+ "num_tokens": 288406.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 1.4316556841135024,
664
+ "epoch": 1.2667946257197698,
665
+ "grad_norm": 1.3814395666122437,
666
+ "learning_rate": 5.96306068601583e-07,
667
+ "loss": 1.3717,
668
+ "mean_token_accuracy": 0.6771419286727905,
669
+ "num_tokens": 292810.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 1.4243345469236375,
674
+ "epoch": 1.2859884836852207,
675
+ "grad_norm": 1.3101155757904053,
676
+ "learning_rate": 5.897097625329816e-07,
677
+ "loss": 1.3458,
678
+ "mean_token_accuracy": 0.675717793405056,
679
+ "num_tokens": 297159.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 1.4271595671772956,
684
+ "epoch": 1.3051823416506718,
685
+ "grad_norm": 1.2887548208236694,
686
+ "learning_rate": 5.8311345646438e-07,
687
+ "loss": 1.3808,
688
+ "mean_token_accuracy": 0.6737751249223948,
689
+ "num_tokens": 301673.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 1.3988382443785667,
694
+ "epoch": 1.3243761996161227,
695
+ "grad_norm": 1.2936028242111206,
696
+ "learning_rate": 5.765171503957783e-07,
697
+ "loss": 1.3466,
698
+ "mean_token_accuracy": 0.6742249563336372,
699
+ "num_tokens": 306011.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 1.4129404231905938,
704
+ "epoch": 1.3435700575815739,
705
+ "grad_norm": 1.365856647491455,
706
+ "learning_rate": 5.699208443271768e-07,
707
+ "loss": 1.4004,
708
+ "mean_token_accuracy": 0.6762094989418983,
709
+ "num_tokens": 310684.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 1.3896265909075738,
714
+ "epoch": 1.362763915547025,
715
+ "grad_norm": 1.480326533317566,
716
+ "learning_rate": 5.633245382585752e-07,
717
+ "loss": 1.3412,
718
+ "mean_token_accuracy": 0.6740002393722534,
719
+ "num_tokens": 314948.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 1.4091107904911042,
724
+ "epoch": 1.381957773512476,
725
+ "grad_norm": 1.2030360698699951,
726
+ "learning_rate": 5.567282321899735e-07,
727
+ "loss": 1.3221,
728
+ "mean_token_accuracy": 0.6703991085290909,
729
+ "num_tokens": 319137.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 1.3776820525527,
734
+ "epoch": 1.401151631477927,
735
+ "grad_norm": 1.3343322277069092,
736
+ "learning_rate": 5.50131926121372e-07,
737
+ "loss": 1.3261,
738
+ "mean_token_accuracy": 0.669080725312233,
739
+ "num_tokens": 323692.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 1.3385411709547044,
744
+ "epoch": 1.420345489443378,
745
+ "grad_norm": 1.508680820465088,
746
+ "learning_rate": 5.435356200527705e-07,
747
+ "loss": 1.3362,
748
+ "mean_token_accuracy": 0.6749741330742836,
749
+ "num_tokens": 328215.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 1.38590829372406,
754
+ "epoch": 1.4395393474088292,
755
+ "grad_norm": 1.2919189929962158,
756
+ "learning_rate": 5.369393139841688e-07,
757
+ "loss": 1.3868,
758
+ "mean_token_accuracy": 0.6657867811620235,
759
+ "num_tokens": 332882.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 1.4047252014279366,
764
+ "epoch": 1.4587332053742803,
765
+ "grad_norm": 1.4611691236495972,
766
+ "learning_rate": 5.303430079155673e-07,
767
+ "loss": 1.4304,
768
+ "mean_token_accuracy": 0.6638705205172301,
769
+ "num_tokens": 337595.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 1.3704433895647525,
774
+ "epoch": 1.4779270633397312,
775
+ "grad_norm": 1.8351633548736572,
776
+ "learning_rate": 5.237467018469657e-07,
777
+ "loss": 1.3722,
778
+ "mean_token_accuracy": 0.6718668848276138,
779
+ "num_tokens": 342172.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 1.406796894967556,
784
+ "epoch": 1.4971209213051824,
785
+ "grad_norm": 1.2843279838562012,
786
+ "learning_rate": 5.17150395778364e-07,
787
+ "loss": 1.4114,
788
+ "mean_token_accuracy": 0.6612038798630238,
789
+ "num_tokens": 346680.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 1.390411025285721,
794
+ "epoch": 1.5163147792706333,
795
+ "grad_norm": 1.371477723121643,
796
+ "learning_rate": 5.105540897097625e-07,
797
+ "loss": 1.3765,
798
+ "mean_token_accuracy": 0.6695740602910518,
799
+ "num_tokens": 351340.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 1.4048142805695534,
804
+ "epoch": 1.5355086372360844,
805
+ "grad_norm": 1.5759378671646118,
806
+ "learning_rate": 5.03957783641161e-07,
807
+ "loss": 1.3774,
808
+ "mean_token_accuracy": 0.6580772455781698,
809
+ "num_tokens": 355725.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 1.3832298710942268,
814
+ "epoch": 1.5547024952015356,
815
+ "grad_norm": 1.3659121990203857,
816
+ "learning_rate": 4.973614775725593e-07,
817
+ "loss": 1.355,
818
+ "mean_token_accuracy": 0.6632212825119496,
819
+ "num_tokens": 360351.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 1.3781431332230567,
824
+ "epoch": 1.5738963531669867,
825
+ "grad_norm": 1.217862844467163,
826
+ "learning_rate": 4.907651715039577e-07,
827
+ "loss": 1.3106,
828
+ "mean_token_accuracy": 0.6837066046893596,
829
+ "num_tokens": 364704.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 1.396301233023405,
834
+ "epoch": 1.5930902111324377,
835
+ "grad_norm": 1.4170340299606323,
836
+ "learning_rate": 4.841688654353562e-07,
837
+ "loss": 1.3848,
838
+ "mean_token_accuracy": 0.6756857700645924,
839
+ "num_tokens": 369223.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 1.3805570371448994,
844
+ "epoch": 1.6122840690978886,
845
+ "grad_norm": 1.6334904432296753,
846
+ "learning_rate": 4.775725593667547e-07,
847
+ "loss": 1.3289,
848
+ "mean_token_accuracy": 0.6720996864140034,
849
+ "num_tokens": 373695.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 1.3304642729461194,
854
+ "epoch": 1.6314779270633397,
855
+ "grad_norm": 1.3716479539871216,
856
+ "learning_rate": 4.70976253298153e-07,
857
+ "loss": 1.358,
858
+ "mean_token_accuracy": 0.6814977154135704,
859
+ "num_tokens": 377944.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 1.325723135471344,
864
+ "epoch": 1.6506717850287909,
865
+ "grad_norm": 1.4637054204940796,
866
+ "learning_rate": 4.6437994722955143e-07,
867
+ "loss": 1.3271,
868
+ "mean_token_accuracy": 0.6779550112783909,
869
+ "num_tokens": 382282.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 1.3619354411959648,
874
+ "epoch": 1.669865642994242,
875
+ "grad_norm": 1.5114948749542236,
876
+ "learning_rate": 4.5778364116094985e-07,
877
+ "loss": 1.3559,
878
+ "mean_token_accuracy": 0.6726201340556145,
879
+ "num_tokens": 386630.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 1.3764189667999744,
884
+ "epoch": 1.689059500959693,
885
+ "grad_norm": 1.5805186033248901,
886
+ "learning_rate": 4.511873350923482e-07,
887
+ "loss": 1.3441,
888
+ "mean_token_accuracy": 0.6739023014903068,
889
+ "num_tokens": 391180.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 1.349490751326084,
894
+ "epoch": 1.7082533589251438,
895
+ "grad_norm": 1.3050271272659302,
896
+ "learning_rate": 4.445910290237467e-07,
897
+ "loss": 1.2895,
898
+ "mean_token_accuracy": 0.6882619224488735,
899
+ "num_tokens": 395271.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 1.3338017553091048,
904
+ "epoch": 1.727447216890595,
905
+ "grad_norm": 1.5821993350982666,
906
+ "learning_rate": 4.379947229551451e-07,
907
+ "loss": 1.3541,
908
+ "mean_token_accuracy": 0.6712648656219244,
909
+ "num_tokens": 399736.0,
910
+ "step": 900
911
+ },
912
+ {
913
+ "entropy": 1.33896948620677,
914
+ "epoch": 1.7466410748560461,
915
+ "grad_norm": 1.3532984256744385,
916
+ "learning_rate": 4.3139841688654347e-07,
917
+ "loss": 1.3286,
918
+ "mean_token_accuracy": 0.6765731774270535,
919
+ "num_tokens": 404242.0,
920
+ "step": 910
921
+ },
922
+ {
923
+ "entropy": 1.3218392327427864,
924
+ "epoch": 1.7658349328214973,
925
+ "grad_norm": 1.502060055732727,
926
+ "learning_rate": 4.2480211081794194e-07,
927
+ "loss": 1.3072,
928
+ "mean_token_accuracy": 0.6809414498507976,
929
+ "num_tokens": 408667.0,
930
+ "step": 920
931
+ },
932
+ {
933
+ "entropy": 1.3454699993133545,
934
+ "epoch": 1.7850287907869482,
935
+ "grad_norm": 1.635991096496582,
936
+ "learning_rate": 4.1820580474934036e-07,
937
+ "loss": 1.2656,
938
+ "mean_token_accuracy": 0.6872869111597538,
939
+ "num_tokens": 412801.0,
940
+ "step": 930
941
+ },
942
+ {
943
+ "entropy": 1.3382192149758338,
944
+ "epoch": 1.8042226487523991,
945
+ "grad_norm": 1.3631840944290161,
946
+ "learning_rate": 4.116094986807387e-07,
947
+ "loss": 1.3583,
948
+ "mean_token_accuracy": 0.6756069511175156,
949
+ "num_tokens": 417242.0,
950
+ "step": 940
951
+ },
952
+ {
953
+ "entropy": 1.2952587850391866,
954
+ "epoch": 1.8234165067178503,
955
+ "grad_norm": 1.482888102531433,
956
+ "learning_rate": 4.050131926121372e-07,
957
+ "loss": 1.2944,
958
+ "mean_token_accuracy": 0.6870723001658916,
959
+ "num_tokens": 421637.0,
960
+ "step": 950
961
+ },
962
+ {
963
+ "entropy": 1.320672082155943,
964
+ "epoch": 1.8426103646833014,
965
+ "grad_norm": 1.3760404586791992,
966
+ "learning_rate": 3.984168865435356e-07,
967
+ "loss": 1.3511,
968
+ "mean_token_accuracy": 0.6759059205651283,
969
+ "num_tokens": 426236.0,
970
+ "step": 960
971
+ },
972
+ {
973
+ "entropy": 1.3185964405536652,
974
+ "epoch": 1.8618042226487526,
975
+ "grad_norm": 1.5384997129440308,
976
+ "learning_rate": 3.91820580474934e-07,
977
+ "loss": 1.2991,
978
+ "mean_token_accuracy": 0.6813853666186332,
979
+ "num_tokens": 430620.0,
980
+ "step": 970
981
+ },
982
+ {
983
+ "entropy": 1.3227439992129804,
984
+ "epoch": 1.8809980806142035,
985
+ "grad_norm": 1.5697379112243652,
986
+ "learning_rate": 3.8522427440633245e-07,
987
+ "loss": 1.3625,
988
+ "mean_token_accuracy": 0.6762081369757652,
989
+ "num_tokens": 435150.0,
990
+ "step": 980
991
+ },
992
+ {
993
+ "entropy": 1.313966491818428,
994
+ "epoch": 1.9001919385796544,
995
+ "grad_norm": 1.3514854907989502,
996
+ "learning_rate": 3.7862796833773087e-07,
997
+ "loss": 1.3263,
998
+ "mean_token_accuracy": 0.6723726324737072,
999
+ "num_tokens": 439647.0,
1000
+ "step": 990
1001
+ },
1002
+ {
1003
+ "entropy": 1.3233631290495396,
1004
+ "epoch": 1.9193857965451055,
1005
+ "grad_norm": 1.386216402053833,
1006
+ "learning_rate": 3.720316622691293e-07,
1007
+ "loss": 1.3127,
1008
+ "mean_token_accuracy": 0.6839993640780448,
1009
+ "num_tokens": 444044.0,
1010
+ "step": 1000
1011
+ },
1012
+ {
1013
+ "entropy": 1.2929065488278866,
1014
+ "epoch": 1.9385796545105567,
1015
+ "grad_norm": 1.392918586730957,
1016
+ "learning_rate": 3.654353562005277e-07,
1017
+ "loss": 1.2789,
1018
+ "mean_token_accuracy": 0.691318365931511,
1019
+ "num_tokens": 448332.0,
1020
+ "step": 1010
1021
+ },
1022
+ {
1023
+ "entropy": 1.2981125928461552,
1024
+ "epoch": 1.9577735124760078,
1025
+ "grad_norm": 1.3615179061889648,
1026
+ "learning_rate": 3.588390501319261e-07,
1027
+ "loss": 1.275,
1028
+ "mean_token_accuracy": 0.68913309648633,
1029
+ "num_tokens": 452630.0,
1030
+ "step": 1020
1031
+ },
1032
+ {
1033
+ "entropy": 1.3281254529953004,
1034
+ "epoch": 1.9769673704414588,
1035
+ "grad_norm": 1.6908109188079834,
1036
+ "learning_rate": 3.5224274406332454e-07,
1037
+ "loss": 1.3256,
1038
+ "mean_token_accuracy": 0.6812291517853737,
1039
+ "num_tokens": 456980.0,
1040
+ "step": 1030
1041
+ },
1042
+ {
1043
+ "entropy": 1.270756483823061,
1044
+ "epoch": 1.9961612284069097,
1045
+ "grad_norm": 1.341234803199768,
1046
+ "learning_rate": 3.456464379947229e-07,
1047
+ "loss": 1.2917,
1048
+ "mean_token_accuracy": 0.6812452055513859,
1049
+ "num_tokens": 461188.0,
1050
+ "step": 1040
1051
+ }
1052
+ ],
1053
+ "logging_steps": 10,
1054
+ "max_steps": 1563,
1055
+ "num_input_tokens_seen": 0,
1056
+ "num_train_epochs": 3,
1057
+ "save_steps": 500,
1058
+ "stateful_callbacks": {
1059
+ "TrainerControl": {
1060
+ "args": {
1061
+ "should_epoch_stop": false,
1062
+ "should_evaluate": false,
1063
+ "should_log": false,
1064
+ "should_save": true,
1065
+ "should_training_stop": false
1066
+ },
1067
+ "attributes": {}
1068
+ }
1069
+ },
1070
+ "total_flos": 1.876450552725504e+16,
1071
+ "train_batch_size": 1,
1072
+ "trial_name": null,
1073
+ "trial_params": null
1074
+ }
justification-only-lora/checkpoint-1042/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a58e27d7a95a1480fb9af6d6f097ae245d2b6f610a857c664827804e835e1957
3
+ size 6417
justification-only-lora/checkpoint-1563/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-2-7b-chat-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:meta-llama/Llama-2-7b-chat-hf
7
+ - lora
8
+ - sft
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
justification-only-lora/checkpoint-1563/adapter_config.json ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
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": 128,
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": 64,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "q_proj",
33
+ "k_proj",
34
+ "v_proj",
35
+ "up_proj",
36
+ "o_proj",
37
+ "down_proj",
38
+ "gate_proj"
39
+ ],
40
+ "target_parameters": null,
41
+ "task_type": "CAUSAL_LM",
42
+ "trainable_token_indices": null,
43
+ "use_dora": false,
44
+ "use_qalora": false,
45
+ "use_rslora": false
46
+ }
justification-only-lora/checkpoint-1563/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1ab80ac53fdda79ab48e10a93f9604688ea4f39ea619486708628153a6303636
3
+ size 639691872
justification-only-lora/checkpoint-1563/chat_template.jinja ADDED
@@ -0,0 +1 @@
 
 
1
+ {% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}
justification-only-lora/checkpoint-1563/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fac1d7c860f68bb606ff1d99d26e071bdbfa79a942a08d6d469cb05fd43cb787
3
+ size 1279641507
justification-only-lora/checkpoint-1563/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f51504fec951007f3a92d997369a383cab54bfd2231401e0467c4ee211867d2b
3
+ size 14645
justification-only-lora/checkpoint-1563/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:161850d0d55886202544d2a8f9fd8a1e21ed54fbd3517d62e4c556f4327e9b7a
3
+ size 1465
justification-only-lora/checkpoint-1563/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
justification-only-lora/checkpoint-1563/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
justification-only-lora/checkpoint-1563/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
justification-only-lora/checkpoint-1563/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": null,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": false,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false
43
+ }
justification-only-lora/checkpoint-1563/trainer_state.json ADDED
@@ -0,0 +1,1594 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 3.0,
6
+ "eval_steps": 500,
7
+ "global_step": 1563,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.5444401994347572,
14
+ "epoch": 0.019193857965451054,
15
+ "grad_norm": 5.821522235870361,
16
+ "learning_rate": 1.9148936170212765e-07,
17
+ "loss": 4.1401,
18
+ "mean_token_accuracy": 0.4060008004307747,
19
+ "num_tokens": 4245.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 1.5042417280375957,
24
+ "epoch": 0.03838771593090211,
25
+ "grad_norm": 5.973490238189697,
26
+ "learning_rate": 4.0425531914893614e-07,
27
+ "loss": 4.0713,
28
+ "mean_token_accuracy": 0.4032037228345871,
29
+ "num_tokens": 8699.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 1.5192734643816947,
34
+ "epoch": 0.05758157389635317,
35
+ "grad_norm": 5.376368999481201,
36
+ "learning_rate": 6.170212765957446e-07,
37
+ "loss": 3.9752,
38
+ "mean_token_accuracy": 0.396929800696671,
39
+ "num_tokens": 13344.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 1.5850717440247535,
44
+ "epoch": 0.07677543186180422,
45
+ "grad_norm": 4.978009223937988,
46
+ "learning_rate": 8.297872340425532e-07,
47
+ "loss": 4.0101,
48
+ "mean_token_accuracy": 0.398511266708374,
49
+ "num_tokens": 17548.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 1.609639537334442,
54
+ "epoch": 0.09596928982725528,
55
+ "grad_norm": 5.168197154998779,
56
+ "learning_rate": 9.986807387862796e-07,
57
+ "loss": 4.0455,
58
+ "mean_token_accuracy": 0.39038523491472005,
59
+ "num_tokens": 21726.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 1.6230455122888088,
64
+ "epoch": 0.11516314779270634,
65
+ "grad_norm": 4.924302577972412,
66
+ "learning_rate": 9.92084432717678e-07,
67
+ "loss": 3.805,
68
+ "mean_token_accuracy": 0.41029399298131464,
69
+ "num_tokens": 26305.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 1.6385258689522744,
74
+ "epoch": 0.1343570057581574,
75
+ "grad_norm": 5.023738861083984,
76
+ "learning_rate": 9.854881266490765e-07,
77
+ "loss": 3.6963,
78
+ "mean_token_accuracy": 0.4034191995859146,
79
+ "num_tokens": 30867.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 1.6791253253817557,
84
+ "epoch": 0.15355086372360843,
85
+ "grad_norm": 4.995085716247559,
86
+ "learning_rate": 9.788918205804749e-07,
87
+ "loss": 3.5687,
88
+ "mean_token_accuracy": 0.41049087755382063,
89
+ "num_tokens": 35488.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 1.7368177756667138,
94
+ "epoch": 0.1727447216890595,
95
+ "grad_norm": 5.233994007110596,
96
+ "learning_rate": 9.722955145118733e-07,
97
+ "loss": 3.502,
98
+ "mean_token_accuracy": 0.41353076659142973,
99
+ "num_tokens": 39905.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 1.7768422558903694,
104
+ "epoch": 0.19193857965451055,
105
+ "grad_norm": 4.299875259399414,
106
+ "learning_rate": 9.656992084432716e-07,
107
+ "loss": 3.4098,
108
+ "mean_token_accuracy": 0.4197281800210476,
109
+ "num_tokens": 44208.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 1.8558007434010506,
114
+ "epoch": 0.21113243761996162,
115
+ "grad_norm": 4.665222644805908,
116
+ "learning_rate": 9.591029023746702e-07,
117
+ "loss": 3.2665,
118
+ "mean_token_accuracy": 0.42318747080862523,
119
+ "num_tokens": 48508.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 1.8271729901432991,
124
+ "epoch": 0.23032629558541268,
125
+ "grad_norm": 3.741534948348999,
126
+ "learning_rate": 9.525065963060686e-07,
127
+ "loss": 3.0302,
128
+ "mean_token_accuracy": 0.4432856226339936,
129
+ "num_tokens": 53006.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 1.855116668343544,
134
+ "epoch": 0.2495201535508637,
135
+ "grad_norm": 3.7163283824920654,
136
+ "learning_rate": 9.459102902374669e-07,
137
+ "loss": 2.9221,
138
+ "mean_token_accuracy": 0.45197133012115953,
139
+ "num_tokens": 57517.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 1.8998430132865907,
144
+ "epoch": 0.2687140115163148,
145
+ "grad_norm": 3.359804153442383,
146
+ "learning_rate": 9.393139841688654e-07,
147
+ "loss": 2.862,
148
+ "mean_token_accuracy": 0.4820567347109318,
149
+ "num_tokens": 61859.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 1.8810108318924903,
154
+ "epoch": 0.28790786948176583,
155
+ "grad_norm": 3.24143648147583,
156
+ "learning_rate": 9.327176781002638e-07,
157
+ "loss": 2.6863,
158
+ "mean_token_accuracy": 0.4882553808391094,
159
+ "num_tokens": 66294.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 1.8664621368050576,
164
+ "epoch": 0.30710172744721687,
165
+ "grad_norm": 3.21515154838562,
166
+ "learning_rate": 9.261213720316622e-07,
167
+ "loss": 2.5571,
168
+ "mean_token_accuracy": 0.4904331646859646,
169
+ "num_tokens": 70881.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 1.9047470435500145,
174
+ "epoch": 0.32629558541266795,
175
+ "grad_norm": 2.9383370876312256,
176
+ "learning_rate": 9.195250659630607e-07,
177
+ "loss": 2.4253,
178
+ "mean_token_accuracy": 0.5186557050794363,
179
+ "num_tokens": 75343.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 1.8957982853055,
184
+ "epoch": 0.345489443378119,
185
+ "grad_norm": 2.855672836303711,
186
+ "learning_rate": 9.129287598944591e-07,
187
+ "loss": 2.3765,
188
+ "mean_token_accuracy": 0.5165872510522604,
189
+ "num_tokens": 79813.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 1.8749225288629532,
194
+ "epoch": 0.3646833013435701,
195
+ "grad_norm": 2.4022603034973145,
196
+ "learning_rate": 9.063324538258574e-07,
197
+ "loss": 2.262,
198
+ "mean_token_accuracy": 0.5304524928331376,
199
+ "num_tokens": 84432.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 1.859298901259899,
204
+ "epoch": 0.3838771593090211,
205
+ "grad_norm": 2.477881908416748,
206
+ "learning_rate": 8.997361477572559e-07,
207
+ "loss": 2.1756,
208
+ "mean_token_accuracy": 0.5431556064635515,
209
+ "num_tokens": 88923.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 1.8629574179649353,
214
+ "epoch": 0.40307101727447214,
215
+ "grad_norm": 2.1476128101348877,
216
+ "learning_rate": 8.931398416886543e-07,
217
+ "loss": 2.1339,
218
+ "mean_token_accuracy": 0.5666973438113928,
219
+ "num_tokens": 93328.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 1.8807074934244157,
224
+ "epoch": 0.42226487523992323,
225
+ "grad_norm": 2.3548238277435303,
226
+ "learning_rate": 8.865435356200526e-07,
227
+ "loss": 2.0982,
228
+ "mean_token_accuracy": 0.5757683675736189,
229
+ "num_tokens": 97899.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 1.9242157697677613,
234
+ "epoch": 0.44145873320537427,
235
+ "grad_norm": 2.224064588546753,
236
+ "learning_rate": 8.799472295514512e-07,
237
+ "loss": 2.0095,
238
+ "mean_token_accuracy": 0.5813840452581645,
239
+ "num_tokens": 102067.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 1.8383784875273705,
244
+ "epoch": 0.46065259117082535,
245
+ "grad_norm": 2.35628604888916,
246
+ "learning_rate": 8.733509234828496e-07,
247
+ "loss": 2.0116,
248
+ "mean_token_accuracy": 0.582221444323659,
249
+ "num_tokens": 106474.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 1.8541715443134308,
254
+ "epoch": 0.4798464491362764,
255
+ "grad_norm": 2.1513049602508545,
256
+ "learning_rate": 8.667546174142479e-07,
257
+ "loss": 1.9723,
258
+ "mean_token_accuracy": 0.591744914278388,
259
+ "num_tokens": 110847.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 1.8240503028035164,
264
+ "epoch": 0.4990403071017274,
265
+ "grad_norm": 1.9908933639526367,
266
+ "learning_rate": 8.601583113456464e-07,
267
+ "loss": 1.9192,
268
+ "mean_token_accuracy": 0.583719938248396,
269
+ "num_tokens": 115237.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 1.8065304696559905,
274
+ "epoch": 0.5182341650671785,
275
+ "grad_norm": 2.1833651065826416,
276
+ "learning_rate": 8.535620052770448e-07,
277
+ "loss": 1.8791,
278
+ "mean_token_accuracy": 0.5988160844892263,
279
+ "num_tokens": 119549.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 1.7882312104105949,
284
+ "epoch": 0.5374280230326296,
285
+ "grad_norm": 2.280733823776245,
286
+ "learning_rate": 8.469656992084431e-07,
287
+ "loss": 1.899,
288
+ "mean_token_accuracy": 0.5769031669944524,
289
+ "num_tokens": 123989.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 1.7919606953859328,
294
+ "epoch": 0.5566218809980806,
295
+ "grad_norm": 2.1053104400634766,
296
+ "learning_rate": 8.403693931398417e-07,
297
+ "loss": 1.833,
298
+ "mean_token_accuracy": 0.5953757733106613,
299
+ "num_tokens": 128278.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 1.8032251179218293,
304
+ "epoch": 0.5758157389635317,
305
+ "grad_norm": 2.0865530967712402,
306
+ "learning_rate": 8.337730870712401e-07,
307
+ "loss": 1.8991,
308
+ "mean_token_accuracy": 0.5826169475913048,
309
+ "num_tokens": 133078.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 1.7583968698978425,
314
+ "epoch": 0.5950095969289827,
315
+ "grad_norm": 1.7579165697097778,
316
+ "learning_rate": 8.271767810026385e-07,
317
+ "loss": 1.7885,
318
+ "mean_token_accuracy": 0.6143867563456297,
319
+ "num_tokens": 137541.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 1.7979290679097175,
324
+ "epoch": 0.6142034548944337,
325
+ "grad_norm": 1.8130688667297363,
326
+ "learning_rate": 8.205804749340369e-07,
327
+ "loss": 1.8252,
328
+ "mean_token_accuracy": 0.6005033150315284,
329
+ "num_tokens": 141810.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 1.7790041908621788,
334
+ "epoch": 0.6333973128598849,
335
+ "grad_norm": 1.9245020151138306,
336
+ "learning_rate": 8.139841688654353e-07,
337
+ "loss": 1.7798,
338
+ "mean_token_accuracy": 0.613793533295393,
339
+ "num_tokens": 146112.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 1.7689658552408218,
344
+ "epoch": 0.6525911708253359,
345
+ "grad_norm": 2.208102226257324,
346
+ "learning_rate": 8.073878627968337e-07,
347
+ "loss": 1.7584,
348
+ "mean_token_accuracy": 0.5983480997383595,
349
+ "num_tokens": 150609.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 1.7603006795048715,
354
+ "epoch": 0.6717850287907869,
355
+ "grad_norm": 1.8552649021148682,
356
+ "learning_rate": 8.007915567282322e-07,
357
+ "loss": 1.7016,
358
+ "mean_token_accuracy": 0.6168740216642619,
359
+ "num_tokens": 155088.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 1.741025310754776,
364
+ "epoch": 0.690978886756238,
365
+ "grad_norm": 1.9795598983764648,
366
+ "learning_rate": 7.941952506596306e-07,
367
+ "loss": 1.7031,
368
+ "mean_token_accuracy": 0.6189993746578694,
369
+ "num_tokens": 159495.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 1.763644915819168,
374
+ "epoch": 0.710172744721689,
375
+ "grad_norm": 2.2528767585754395,
376
+ "learning_rate": 7.87598944591029e-07,
377
+ "loss": 1.6961,
378
+ "mean_token_accuracy": 0.6185917239636183,
379
+ "num_tokens": 163793.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 1.739506982266903,
384
+ "epoch": 0.7293666026871402,
385
+ "grad_norm": 1.9315766096115112,
386
+ "learning_rate": 7.810026385224274e-07,
387
+ "loss": 1.6339,
388
+ "mean_token_accuracy": 0.6323129627853632,
389
+ "num_tokens": 168268.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 1.7659575924277306,
394
+ "epoch": 0.7485604606525912,
395
+ "grad_norm": 1.8060170412063599,
396
+ "learning_rate": 7.744063324538258e-07,
397
+ "loss": 1.6461,
398
+ "mean_token_accuracy": 0.6334325969219208,
399
+ "num_tokens": 172612.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 1.7049371361732484,
404
+ "epoch": 0.7677543186180422,
405
+ "grad_norm": 1.7351154088974,
406
+ "learning_rate": 7.678100263852242e-07,
407
+ "loss": 1.5584,
408
+ "mean_token_accuracy": 0.64255366101861,
409
+ "num_tokens": 176987.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 1.6969178169965744,
414
+ "epoch": 0.7869481765834933,
415
+ "grad_norm": 1.5524696111679077,
416
+ "learning_rate": 7.612137203166226e-07,
417
+ "loss": 1.6435,
418
+ "mean_token_accuracy": 0.632745499163866,
419
+ "num_tokens": 181538.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 1.6801453217864037,
424
+ "epoch": 0.8061420345489443,
425
+ "grad_norm": 1.667938470840454,
426
+ "learning_rate": 7.546174142480211e-07,
427
+ "loss": 1.5851,
428
+ "mean_token_accuracy": 0.6391880080103874,
429
+ "num_tokens": 185819.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 1.6663354828953743,
434
+ "epoch": 0.8253358925143954,
435
+ "grad_norm": 1.5086743831634521,
436
+ "learning_rate": 7.480211081794196e-07,
437
+ "loss": 1.5759,
438
+ "mean_token_accuracy": 0.6453739482909441,
439
+ "num_tokens": 190254.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 1.6495836034417153,
444
+ "epoch": 0.8445297504798465,
445
+ "grad_norm": 1.7330267429351807,
446
+ "learning_rate": 7.414248021108179e-07,
447
+ "loss": 1.5403,
448
+ "mean_token_accuracy": 0.6486042737960815,
449
+ "num_tokens": 194643.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 1.6953262895345689,
454
+ "epoch": 0.8637236084452975,
455
+ "grad_norm": 1.465407133102417,
456
+ "learning_rate": 7.348284960422163e-07,
457
+ "loss": 1.5757,
458
+ "mean_token_accuracy": 0.6440861701965332,
459
+ "num_tokens": 198983.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 1.6009652018547058,
464
+ "epoch": 0.8829174664107485,
465
+ "grad_norm": 1.484931230545044,
466
+ "learning_rate": 7.282321899736148e-07,
467
+ "loss": 1.4547,
468
+ "mean_token_accuracy": 0.6605511672794819,
469
+ "num_tokens": 203270.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 1.6046269670128823,
474
+ "epoch": 0.9021113243761996,
475
+ "grad_norm": 1.4576069116592407,
476
+ "learning_rate": 7.216358839050131e-07,
477
+ "loss": 1.5508,
478
+ "mean_token_accuracy": 0.6439322311431169,
479
+ "num_tokens": 207696.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 1.6068053118884564,
484
+ "epoch": 0.9213051823416507,
485
+ "grad_norm": 1.7096375226974487,
486
+ "learning_rate": 7.150395778364116e-07,
487
+ "loss": 1.5665,
488
+ "mean_token_accuracy": 0.6389439355581998,
489
+ "num_tokens": 212574.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 1.58553556650877,
494
+ "epoch": 0.9404990403071017,
495
+ "grad_norm": 1.8892183303833008,
496
+ "learning_rate": 7.084432717678101e-07,
497
+ "loss": 1.5476,
498
+ "mean_token_accuracy": 0.6533854089677333,
499
+ "num_tokens": 217308.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 1.6013462141156196,
504
+ "epoch": 0.9596928982725528,
505
+ "grad_norm": 1.3890715837478638,
506
+ "learning_rate": 7.018469656992084e-07,
507
+ "loss": 1.5067,
508
+ "mean_token_accuracy": 0.6439886368811131,
509
+ "num_tokens": 221638.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 1.5622883230447768,
514
+ "epoch": 0.9788867562380038,
515
+ "grad_norm": 1.4576449394226074,
516
+ "learning_rate": 6.952506596306068e-07,
517
+ "loss": 1.5282,
518
+ "mean_token_accuracy": 0.6542089767754078,
519
+ "num_tokens": 226264.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 1.5611482337117195,
524
+ "epoch": 0.9980806142034548,
525
+ "grad_norm": 1.3677759170532227,
526
+ "learning_rate": 6.886543535620053e-07,
527
+ "loss": 1.4478,
528
+ "mean_token_accuracy": 0.6510695222765207,
529
+ "num_tokens": 230675.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 1.5630412474274635,
534
+ "epoch": 1.017274472168906,
535
+ "grad_norm": 1.451343297958374,
536
+ "learning_rate": 6.820580474934036e-07,
537
+ "loss": 1.5144,
538
+ "mean_token_accuracy": 0.6554066635668278,
539
+ "num_tokens": 235290.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 1.5062206633388997,
544
+ "epoch": 1.036468330134357,
545
+ "grad_norm": 1.4385675191879272,
546
+ "learning_rate": 6.75461741424802e-07,
547
+ "loss": 1.459,
548
+ "mean_token_accuracy": 0.6650427110493183,
549
+ "num_tokens": 239682.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 1.5518377706408502,
554
+ "epoch": 1.055662188099808,
555
+ "grad_norm": 1.3765565156936646,
556
+ "learning_rate": 6.688654353562006e-07,
557
+ "loss": 1.5403,
558
+ "mean_token_accuracy": 0.6449352588504553,
559
+ "num_tokens": 244138.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 1.5200361490249634,
564
+ "epoch": 1.0748560460652592,
565
+ "grad_norm": 1.356392741203308,
566
+ "learning_rate": 6.62269129287599e-07,
567
+ "loss": 1.4413,
568
+ "mean_token_accuracy": 0.6655519589781761,
569
+ "num_tokens": 248375.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 1.517387817800045,
574
+ "epoch": 1.0940499040307101,
575
+ "grad_norm": 1.2830088138580322,
576
+ "learning_rate": 6.556728232189973e-07,
577
+ "loss": 1.4174,
578
+ "mean_token_accuracy": 0.658090665563941,
579
+ "num_tokens": 252941.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 1.4819800563156604,
584
+ "epoch": 1.1132437619961613,
585
+ "grad_norm": 1.4165180921554565,
586
+ "learning_rate": 6.490765171503958e-07,
587
+ "loss": 1.4804,
588
+ "mean_token_accuracy": 0.6585468038916588,
589
+ "num_tokens": 257486.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 1.5246448263525962,
594
+ "epoch": 1.1324376199616122,
595
+ "grad_norm": 1.3312668800354004,
596
+ "learning_rate": 6.424802110817942e-07,
597
+ "loss": 1.473,
598
+ "mean_token_accuracy": 0.652620742097497,
599
+ "num_tokens": 261978.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 1.489580862224102,
604
+ "epoch": 1.1516314779270633,
605
+ "grad_norm": 1.2045397758483887,
606
+ "learning_rate": 6.358839050131925e-07,
607
+ "loss": 1.3997,
608
+ "mean_token_accuracy": 0.6628001451492309,
609
+ "num_tokens": 266337.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 1.49830242395401,
614
+ "epoch": 1.1708253358925145,
615
+ "grad_norm": 1.4452189207077026,
616
+ "learning_rate": 6.292875989445911e-07,
617
+ "loss": 1.4246,
618
+ "mean_token_accuracy": 0.6613333437591791,
619
+ "num_tokens": 270625.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 1.477701984345913,
624
+ "epoch": 1.1900191938579654,
625
+ "grad_norm": 1.4515446424484253,
626
+ "learning_rate": 6.226912928759895e-07,
627
+ "loss": 1.4386,
628
+ "mean_token_accuracy": 0.666374447196722,
629
+ "num_tokens": 274970.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 1.4627806089818478,
634
+ "epoch": 1.2092130518234165,
635
+ "grad_norm": 1.2604293823242188,
636
+ "learning_rate": 6.160949868073878e-07,
637
+ "loss": 1.4076,
638
+ "mean_token_accuracy": 0.6598449043929577,
639
+ "num_tokens": 279480.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 1.435338243842125,
644
+ "epoch": 1.2284069097888675,
645
+ "grad_norm": 1.2244068384170532,
646
+ "learning_rate": 6.094986807387863e-07,
647
+ "loss": 1.3863,
648
+ "mean_token_accuracy": 0.66046132594347,
649
+ "num_tokens": 283918.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 1.459252581000328,
654
+ "epoch": 1.2476007677543186,
655
+ "grad_norm": 1.3843801021575928,
656
+ "learning_rate": 6.029023746701847e-07,
657
+ "loss": 1.4447,
658
+ "mean_token_accuracy": 0.653592013567686,
659
+ "num_tokens": 288406.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 1.4316556841135024,
664
+ "epoch": 1.2667946257197698,
665
+ "grad_norm": 1.3814395666122437,
666
+ "learning_rate": 5.96306068601583e-07,
667
+ "loss": 1.3717,
668
+ "mean_token_accuracy": 0.6771419286727905,
669
+ "num_tokens": 292810.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 1.4243345469236375,
674
+ "epoch": 1.2859884836852207,
675
+ "grad_norm": 1.3101155757904053,
676
+ "learning_rate": 5.897097625329816e-07,
677
+ "loss": 1.3458,
678
+ "mean_token_accuracy": 0.675717793405056,
679
+ "num_tokens": 297159.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 1.4271595671772956,
684
+ "epoch": 1.3051823416506718,
685
+ "grad_norm": 1.2887548208236694,
686
+ "learning_rate": 5.8311345646438e-07,
687
+ "loss": 1.3808,
688
+ "mean_token_accuracy": 0.6737751249223948,
689
+ "num_tokens": 301673.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 1.3988382443785667,
694
+ "epoch": 1.3243761996161227,
695
+ "grad_norm": 1.2936028242111206,
696
+ "learning_rate": 5.765171503957783e-07,
697
+ "loss": 1.3466,
698
+ "mean_token_accuracy": 0.6742249563336372,
699
+ "num_tokens": 306011.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 1.4129404231905938,
704
+ "epoch": 1.3435700575815739,
705
+ "grad_norm": 1.365856647491455,
706
+ "learning_rate": 5.699208443271768e-07,
707
+ "loss": 1.4004,
708
+ "mean_token_accuracy": 0.6762094989418983,
709
+ "num_tokens": 310684.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 1.3896265909075738,
714
+ "epoch": 1.362763915547025,
715
+ "grad_norm": 1.480326533317566,
716
+ "learning_rate": 5.633245382585752e-07,
717
+ "loss": 1.3412,
718
+ "mean_token_accuracy": 0.6740002393722534,
719
+ "num_tokens": 314948.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 1.4091107904911042,
724
+ "epoch": 1.381957773512476,
725
+ "grad_norm": 1.2030360698699951,
726
+ "learning_rate": 5.567282321899735e-07,
727
+ "loss": 1.3221,
728
+ "mean_token_accuracy": 0.6703991085290909,
729
+ "num_tokens": 319137.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 1.3776820525527,
734
+ "epoch": 1.401151631477927,
735
+ "grad_norm": 1.3343322277069092,
736
+ "learning_rate": 5.50131926121372e-07,
737
+ "loss": 1.3261,
738
+ "mean_token_accuracy": 0.669080725312233,
739
+ "num_tokens": 323692.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 1.3385411709547044,
744
+ "epoch": 1.420345489443378,
745
+ "grad_norm": 1.508680820465088,
746
+ "learning_rate": 5.435356200527705e-07,
747
+ "loss": 1.3362,
748
+ "mean_token_accuracy": 0.6749741330742836,
749
+ "num_tokens": 328215.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 1.38590829372406,
754
+ "epoch": 1.4395393474088292,
755
+ "grad_norm": 1.2919189929962158,
756
+ "learning_rate": 5.369393139841688e-07,
757
+ "loss": 1.3868,
758
+ "mean_token_accuracy": 0.6657867811620235,
759
+ "num_tokens": 332882.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 1.4047252014279366,
764
+ "epoch": 1.4587332053742803,
765
+ "grad_norm": 1.4611691236495972,
766
+ "learning_rate": 5.303430079155673e-07,
767
+ "loss": 1.4304,
768
+ "mean_token_accuracy": 0.6638705205172301,
769
+ "num_tokens": 337595.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 1.3704433895647525,
774
+ "epoch": 1.4779270633397312,
775
+ "grad_norm": 1.8351633548736572,
776
+ "learning_rate": 5.237467018469657e-07,
777
+ "loss": 1.3722,
778
+ "mean_token_accuracy": 0.6718668848276138,
779
+ "num_tokens": 342172.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 1.406796894967556,
784
+ "epoch": 1.4971209213051824,
785
+ "grad_norm": 1.2843279838562012,
786
+ "learning_rate": 5.17150395778364e-07,
787
+ "loss": 1.4114,
788
+ "mean_token_accuracy": 0.6612038798630238,
789
+ "num_tokens": 346680.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 1.390411025285721,
794
+ "epoch": 1.5163147792706333,
795
+ "grad_norm": 1.371477723121643,
796
+ "learning_rate": 5.105540897097625e-07,
797
+ "loss": 1.3765,
798
+ "mean_token_accuracy": 0.6695740602910518,
799
+ "num_tokens": 351340.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 1.4048142805695534,
804
+ "epoch": 1.5355086372360844,
805
+ "grad_norm": 1.5759378671646118,
806
+ "learning_rate": 5.03957783641161e-07,
807
+ "loss": 1.3774,
808
+ "mean_token_accuracy": 0.6580772455781698,
809
+ "num_tokens": 355725.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 1.3832298710942268,
814
+ "epoch": 1.5547024952015356,
815
+ "grad_norm": 1.3659121990203857,
816
+ "learning_rate": 4.973614775725593e-07,
817
+ "loss": 1.355,
818
+ "mean_token_accuracy": 0.6632212825119496,
819
+ "num_tokens": 360351.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 1.3781431332230567,
824
+ "epoch": 1.5738963531669867,
825
+ "grad_norm": 1.217862844467163,
826
+ "learning_rate": 4.907651715039577e-07,
827
+ "loss": 1.3106,
828
+ "mean_token_accuracy": 0.6837066046893596,
829
+ "num_tokens": 364704.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 1.396301233023405,
834
+ "epoch": 1.5930902111324377,
835
+ "grad_norm": 1.4170340299606323,
836
+ "learning_rate": 4.841688654353562e-07,
837
+ "loss": 1.3848,
838
+ "mean_token_accuracy": 0.6756857700645924,
839
+ "num_tokens": 369223.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 1.3805570371448994,
844
+ "epoch": 1.6122840690978886,
845
+ "grad_norm": 1.6334904432296753,
846
+ "learning_rate": 4.775725593667547e-07,
847
+ "loss": 1.3289,
848
+ "mean_token_accuracy": 0.6720996864140034,
849
+ "num_tokens": 373695.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 1.3304642729461194,
854
+ "epoch": 1.6314779270633397,
855
+ "grad_norm": 1.3716479539871216,
856
+ "learning_rate": 4.70976253298153e-07,
857
+ "loss": 1.358,
858
+ "mean_token_accuracy": 0.6814977154135704,
859
+ "num_tokens": 377944.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 1.325723135471344,
864
+ "epoch": 1.6506717850287909,
865
+ "grad_norm": 1.4637054204940796,
866
+ "learning_rate": 4.6437994722955143e-07,
867
+ "loss": 1.3271,
868
+ "mean_token_accuracy": 0.6779550112783909,
869
+ "num_tokens": 382282.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 1.3619354411959648,
874
+ "epoch": 1.669865642994242,
875
+ "grad_norm": 1.5114948749542236,
876
+ "learning_rate": 4.5778364116094985e-07,
877
+ "loss": 1.3559,
878
+ "mean_token_accuracy": 0.6726201340556145,
879
+ "num_tokens": 386630.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 1.3764189667999744,
884
+ "epoch": 1.689059500959693,
885
+ "grad_norm": 1.5805186033248901,
886
+ "learning_rate": 4.511873350923482e-07,
887
+ "loss": 1.3441,
888
+ "mean_token_accuracy": 0.6739023014903068,
889
+ "num_tokens": 391180.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 1.349490751326084,
894
+ "epoch": 1.7082533589251438,
895
+ "grad_norm": 1.3050271272659302,
896
+ "learning_rate": 4.445910290237467e-07,
897
+ "loss": 1.2895,
898
+ "mean_token_accuracy": 0.6882619224488735,
899
+ "num_tokens": 395271.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 1.3338017553091048,
904
+ "epoch": 1.727447216890595,
905
+ "grad_norm": 1.5821993350982666,
906
+ "learning_rate": 4.379947229551451e-07,
907
+ "loss": 1.3541,
908
+ "mean_token_accuracy": 0.6712648656219244,
909
+ "num_tokens": 399736.0,
910
+ "step": 900
911
+ },
912
+ {
913
+ "entropy": 1.33896948620677,
914
+ "epoch": 1.7466410748560461,
915
+ "grad_norm": 1.3532984256744385,
916
+ "learning_rate": 4.3139841688654347e-07,
917
+ "loss": 1.3286,
918
+ "mean_token_accuracy": 0.6765731774270535,
919
+ "num_tokens": 404242.0,
920
+ "step": 910
921
+ },
922
+ {
923
+ "entropy": 1.3218392327427864,
924
+ "epoch": 1.7658349328214973,
925
+ "grad_norm": 1.502060055732727,
926
+ "learning_rate": 4.2480211081794194e-07,
927
+ "loss": 1.3072,
928
+ "mean_token_accuracy": 0.6809414498507976,
929
+ "num_tokens": 408667.0,
930
+ "step": 920
931
+ },
932
+ {
933
+ "entropy": 1.3454699993133545,
934
+ "epoch": 1.7850287907869482,
935
+ "grad_norm": 1.635991096496582,
936
+ "learning_rate": 4.1820580474934036e-07,
937
+ "loss": 1.2656,
938
+ "mean_token_accuracy": 0.6872869111597538,
939
+ "num_tokens": 412801.0,
940
+ "step": 930
941
+ },
942
+ {
943
+ "entropy": 1.3382192149758338,
944
+ "epoch": 1.8042226487523991,
945
+ "grad_norm": 1.3631840944290161,
946
+ "learning_rate": 4.116094986807387e-07,
947
+ "loss": 1.3583,
948
+ "mean_token_accuracy": 0.6756069511175156,
949
+ "num_tokens": 417242.0,
950
+ "step": 940
951
+ },
952
+ {
953
+ "entropy": 1.2952587850391866,
954
+ "epoch": 1.8234165067178503,
955
+ "grad_norm": 1.482888102531433,
956
+ "learning_rate": 4.050131926121372e-07,
957
+ "loss": 1.2944,
958
+ "mean_token_accuracy": 0.6870723001658916,
959
+ "num_tokens": 421637.0,
960
+ "step": 950
961
+ },
962
+ {
963
+ "entropy": 1.320672082155943,
964
+ "epoch": 1.8426103646833014,
965
+ "grad_norm": 1.3760404586791992,
966
+ "learning_rate": 3.984168865435356e-07,
967
+ "loss": 1.3511,
968
+ "mean_token_accuracy": 0.6759059205651283,
969
+ "num_tokens": 426236.0,
970
+ "step": 960
971
+ },
972
+ {
973
+ "entropy": 1.3185964405536652,
974
+ "epoch": 1.8618042226487526,
975
+ "grad_norm": 1.5384997129440308,
976
+ "learning_rate": 3.91820580474934e-07,
977
+ "loss": 1.2991,
978
+ "mean_token_accuracy": 0.6813853666186332,
979
+ "num_tokens": 430620.0,
980
+ "step": 970
981
+ },
982
+ {
983
+ "entropy": 1.3227439992129804,
984
+ "epoch": 1.8809980806142035,
985
+ "grad_norm": 1.5697379112243652,
986
+ "learning_rate": 3.8522427440633245e-07,
987
+ "loss": 1.3625,
988
+ "mean_token_accuracy": 0.6762081369757652,
989
+ "num_tokens": 435150.0,
990
+ "step": 980
991
+ },
992
+ {
993
+ "entropy": 1.313966491818428,
994
+ "epoch": 1.9001919385796544,
995
+ "grad_norm": 1.3514854907989502,
996
+ "learning_rate": 3.7862796833773087e-07,
997
+ "loss": 1.3263,
998
+ "mean_token_accuracy": 0.6723726324737072,
999
+ "num_tokens": 439647.0,
1000
+ "step": 990
1001
+ },
1002
+ {
1003
+ "entropy": 1.3233631290495396,
1004
+ "epoch": 1.9193857965451055,
1005
+ "grad_norm": 1.386216402053833,
1006
+ "learning_rate": 3.720316622691293e-07,
1007
+ "loss": 1.3127,
1008
+ "mean_token_accuracy": 0.6839993640780448,
1009
+ "num_tokens": 444044.0,
1010
+ "step": 1000
1011
+ },
1012
+ {
1013
+ "entropy": 1.2929065488278866,
1014
+ "epoch": 1.9385796545105567,
1015
+ "grad_norm": 1.392918586730957,
1016
+ "learning_rate": 3.654353562005277e-07,
1017
+ "loss": 1.2789,
1018
+ "mean_token_accuracy": 0.691318365931511,
1019
+ "num_tokens": 448332.0,
1020
+ "step": 1010
1021
+ },
1022
+ {
1023
+ "entropy": 1.2981125928461552,
1024
+ "epoch": 1.9577735124760078,
1025
+ "grad_norm": 1.3615179061889648,
1026
+ "learning_rate": 3.588390501319261e-07,
1027
+ "loss": 1.275,
1028
+ "mean_token_accuracy": 0.68913309648633,
1029
+ "num_tokens": 452630.0,
1030
+ "step": 1020
1031
+ },
1032
+ {
1033
+ "entropy": 1.3281254529953004,
1034
+ "epoch": 1.9769673704414588,
1035
+ "grad_norm": 1.6908109188079834,
1036
+ "learning_rate": 3.5224274406332454e-07,
1037
+ "loss": 1.3256,
1038
+ "mean_token_accuracy": 0.6812291517853737,
1039
+ "num_tokens": 456980.0,
1040
+ "step": 1030
1041
+ },
1042
+ {
1043
+ "entropy": 1.270756483823061,
1044
+ "epoch": 1.9961612284069097,
1045
+ "grad_norm": 1.341234803199768,
1046
+ "learning_rate": 3.456464379947229e-07,
1047
+ "loss": 1.2917,
1048
+ "mean_token_accuracy": 0.6812452055513859,
1049
+ "num_tokens": 461188.0,
1050
+ "step": 1040
1051
+ },
1052
+ {
1053
+ "entropy": 1.3435936361551284,
1054
+ "epoch": 2.015355086372361,
1055
+ "grad_norm": 1.4235236644744873,
1056
+ "learning_rate": 3.390501319261214e-07,
1057
+ "loss": 1.3605,
1058
+ "mean_token_accuracy": 0.6668237581849098,
1059
+ "num_tokens": 465819.0,
1060
+ "step": 1050
1061
+ },
1062
+ {
1063
+ "entropy": 1.3232629679143428,
1064
+ "epoch": 2.034548944337812,
1065
+ "grad_norm": 1.283897042274475,
1066
+ "learning_rate": 3.324538258575198e-07,
1067
+ "loss": 1.3002,
1068
+ "mean_token_accuracy": 0.6775508165359497,
1069
+ "num_tokens": 470479.0,
1070
+ "step": 1060
1071
+ },
1072
+ {
1073
+ "entropy": 1.3024720832705499,
1074
+ "epoch": 2.053742802303263,
1075
+ "grad_norm": 1.5201691389083862,
1076
+ "learning_rate": 3.2585751978891816e-07,
1077
+ "loss": 1.3144,
1078
+ "mean_token_accuracy": 0.6828004539012908,
1079
+ "num_tokens": 474805.0,
1080
+ "step": 1070
1081
+ },
1082
+ {
1083
+ "entropy": 1.3122016772627831,
1084
+ "epoch": 2.072936660268714,
1085
+ "grad_norm": 1.4469714164733887,
1086
+ "learning_rate": 3.1926121372031663e-07,
1087
+ "loss": 1.3494,
1088
+ "mean_token_accuracy": 0.6670678146183491,
1089
+ "num_tokens": 479352.0,
1090
+ "step": 1080
1091
+ },
1092
+ {
1093
+ "entropy": 1.3177859008312225,
1094
+ "epoch": 2.092130518234165,
1095
+ "grad_norm": 1.5209486484527588,
1096
+ "learning_rate": 3.1266490765171505e-07,
1097
+ "loss": 1.3266,
1098
+ "mean_token_accuracy": 0.6678531132638454,
1099
+ "num_tokens": 483927.0,
1100
+ "step": 1090
1101
+ },
1102
+ {
1103
+ "entropy": 1.3064551755785943,
1104
+ "epoch": 2.111324376199616,
1105
+ "grad_norm": 1.481791377067566,
1106
+ "learning_rate": 3.060686015831134e-07,
1107
+ "loss": 1.3206,
1108
+ "mean_token_accuracy": 0.6830546356737613,
1109
+ "num_tokens": 488341.0,
1110
+ "step": 1100
1111
+ },
1112
+ {
1113
+ "entropy": 1.319955986738205,
1114
+ "epoch": 2.1305182341650672,
1115
+ "grad_norm": 1.3968640565872192,
1116
+ "learning_rate": 2.994722955145119e-07,
1117
+ "loss": 1.3302,
1118
+ "mean_token_accuracy": 0.673691725730896,
1119
+ "num_tokens": 492977.0,
1120
+ "step": 1110
1121
+ },
1122
+ {
1123
+ "entropy": 1.2600168503820897,
1124
+ "epoch": 2.1497120921305184,
1125
+ "grad_norm": 1.2328168153762817,
1126
+ "learning_rate": 2.928759894459103e-07,
1127
+ "loss": 1.2241,
1128
+ "mean_token_accuracy": 0.7017722100019455,
1129
+ "num_tokens": 497276.0,
1130
+ "step": 1120
1131
+ },
1132
+ {
1133
+ "entropy": 1.3103215247392654,
1134
+ "epoch": 2.168905950095969,
1135
+ "grad_norm": 1.6284279823303223,
1136
+ "learning_rate": 2.8627968337730866e-07,
1137
+ "loss": 1.357,
1138
+ "mean_token_accuracy": 0.6668395400047302,
1139
+ "num_tokens": 502047.0,
1140
+ "step": 1130
1141
+ },
1142
+ {
1143
+ "entropy": 1.3090356536209584,
1144
+ "epoch": 2.1880998080614202,
1145
+ "grad_norm": 1.33568274974823,
1146
+ "learning_rate": 2.7968337730870713e-07,
1147
+ "loss": 1.3238,
1148
+ "mean_token_accuracy": 0.6725661128759384,
1149
+ "num_tokens": 506762.0,
1150
+ "step": 1140
1151
+ },
1152
+ {
1153
+ "entropy": 1.3052120059728622,
1154
+ "epoch": 2.2072936660268714,
1155
+ "grad_norm": 1.2979674339294434,
1156
+ "learning_rate": 2.7308707124010555e-07,
1157
+ "loss": 1.2406,
1158
+ "mean_token_accuracy": 0.6894351080060005,
1159
+ "num_tokens": 510932.0,
1160
+ "step": 1150
1161
+ },
1162
+ {
1163
+ "entropy": 1.2998326949775219,
1164
+ "epoch": 2.2264875239923225,
1165
+ "grad_norm": 1.3089884519577026,
1166
+ "learning_rate": 2.664907651715039e-07,
1167
+ "loss": 1.3153,
1168
+ "mean_token_accuracy": 0.6822940424084664,
1169
+ "num_tokens": 515427.0,
1170
+ "step": 1160
1171
+ },
1172
+ {
1173
+ "entropy": 1.2902531705796718,
1174
+ "epoch": 2.2456813819577737,
1175
+ "grad_norm": 1.517556071281433,
1176
+ "learning_rate": 2.598944591029024e-07,
1177
+ "loss": 1.3025,
1178
+ "mean_token_accuracy": 0.6799394376575947,
1179
+ "num_tokens": 519836.0,
1180
+ "step": 1170
1181
+ },
1182
+ {
1183
+ "entropy": 1.28161414116621,
1184
+ "epoch": 2.2648752399232244,
1185
+ "grad_norm": 1.4088398218154907,
1186
+ "learning_rate": 2.532981530343008e-07,
1187
+ "loss": 1.294,
1188
+ "mean_token_accuracy": 0.688885697722435,
1189
+ "num_tokens": 524133.0,
1190
+ "step": 1180
1191
+ },
1192
+ {
1193
+ "entropy": 1.2472076505422591,
1194
+ "epoch": 2.2840690978886755,
1195
+ "grad_norm": 1.335199236869812,
1196
+ "learning_rate": 2.467018469656992e-07,
1197
+ "loss": 1.2884,
1198
+ "mean_token_accuracy": 0.7036932289600373,
1199
+ "num_tokens": 528563.0,
1200
+ "step": 1190
1201
+ },
1202
+ {
1203
+ "entropy": 1.28983159288764,
1204
+ "epoch": 2.3032629558541267,
1205
+ "grad_norm": 1.5047142505645752,
1206
+ "learning_rate": 2.401055408970976e-07,
1207
+ "loss": 1.2767,
1208
+ "mean_token_accuracy": 0.6936770267784595,
1209
+ "num_tokens": 532912.0,
1210
+ "step": 1200
1211
+ },
1212
+ {
1213
+ "entropy": 1.297673599421978,
1214
+ "epoch": 2.322456813819578,
1215
+ "grad_norm": 1.549764633178711,
1216
+ "learning_rate": 2.3350923482849603e-07,
1217
+ "loss": 1.3228,
1218
+ "mean_token_accuracy": 0.6820710323750973,
1219
+ "num_tokens": 537148.0,
1220
+ "step": 1210
1221
+ },
1222
+ {
1223
+ "entropy": 1.2781125754117966,
1224
+ "epoch": 2.341650671785029,
1225
+ "grad_norm": 1.3268665075302124,
1226
+ "learning_rate": 2.2691292875989445e-07,
1227
+ "loss": 1.2659,
1228
+ "mean_token_accuracy": 0.6883464485406876,
1229
+ "num_tokens": 541587.0,
1230
+ "step": 1220
1231
+ },
1232
+ {
1233
+ "entropy": 1.298785186558962,
1234
+ "epoch": 2.36084452975048,
1235
+ "grad_norm": 1.3351597785949707,
1236
+ "learning_rate": 2.2031662269129287e-07,
1237
+ "loss": 1.2907,
1238
+ "mean_token_accuracy": 0.6870604187250138,
1239
+ "num_tokens": 546082.0,
1240
+ "step": 1230
1241
+ },
1242
+ {
1243
+ "entropy": 1.31799146682024,
1244
+ "epoch": 2.380038387715931,
1245
+ "grad_norm": 1.2907146215438843,
1246
+ "learning_rate": 2.1372031662269126e-07,
1247
+ "loss": 1.3539,
1248
+ "mean_token_accuracy": 0.6757581025362015,
1249
+ "num_tokens": 550875.0,
1250
+ "step": 1240
1251
+ },
1252
+ {
1253
+ "entropy": 1.2937058471143246,
1254
+ "epoch": 2.399232245681382,
1255
+ "grad_norm": 1.2982598543167114,
1256
+ "learning_rate": 2.071240105540897e-07,
1257
+ "loss": 1.3177,
1258
+ "mean_token_accuracy": 0.670148654282093,
1259
+ "num_tokens": 555402.0,
1260
+ "step": 1250
1261
+ },
1262
+ {
1263
+ "entropy": 1.3055342875421048,
1264
+ "epoch": 2.418426103646833,
1265
+ "grad_norm": 1.4015284776687622,
1266
+ "learning_rate": 2.0052770448548812e-07,
1267
+ "loss": 1.2447,
1268
+ "mean_token_accuracy": 0.6907467879354954,
1269
+ "num_tokens": 559642.0,
1270
+ "step": 1260
1271
+ },
1272
+ {
1273
+ "entropy": 1.3008297756314278,
1274
+ "epoch": 2.4376199616122842,
1275
+ "grad_norm": 1.299880027770996,
1276
+ "learning_rate": 1.9393139841688651e-07,
1277
+ "loss": 1.3264,
1278
+ "mean_token_accuracy": 0.6823808416724205,
1279
+ "num_tokens": 563954.0,
1280
+ "step": 1270
1281
+ },
1282
+ {
1283
+ "entropy": 1.307408395409584,
1284
+ "epoch": 2.456813819577735,
1285
+ "grad_norm": 1.2731596231460571,
1286
+ "learning_rate": 1.8733509234828496e-07,
1287
+ "loss": 1.3463,
1288
+ "mean_token_accuracy": 0.6831272788345814,
1289
+ "num_tokens": 568695.0,
1290
+ "step": 1280
1291
+ },
1292
+ {
1293
+ "entropy": 1.3174359016120434,
1294
+ "epoch": 2.476007677543186,
1295
+ "grad_norm": 1.5982757806777954,
1296
+ "learning_rate": 1.8073878627968338e-07,
1297
+ "loss": 1.3569,
1298
+ "mean_token_accuracy": 0.6847067341208458,
1299
+ "num_tokens": 573312.0,
1300
+ "step": 1290
1301
+ },
1302
+ {
1303
+ "entropy": 1.3000279910862447,
1304
+ "epoch": 2.495201535508637,
1305
+ "grad_norm": 1.3823977708816528,
1306
+ "learning_rate": 1.741424802110818e-07,
1307
+ "loss": 1.2666,
1308
+ "mean_token_accuracy": 0.696950975805521,
1309
+ "num_tokens": 577626.0,
1310
+ "step": 1300
1311
+ },
1312
+ {
1313
+ "entropy": 1.2941087260842323,
1314
+ "epoch": 2.5143953934740884,
1315
+ "grad_norm": 1.3794970512390137,
1316
+ "learning_rate": 1.675461741424802e-07,
1317
+ "loss": 1.3124,
1318
+ "mean_token_accuracy": 0.6803482968360186,
1319
+ "num_tokens": 582044.0,
1320
+ "step": 1310
1321
+ },
1322
+ {
1323
+ "entropy": 1.2815818771719933,
1324
+ "epoch": 2.5335892514395395,
1325
+ "grad_norm": 1.3148255348205566,
1326
+ "learning_rate": 1.609498680738786e-07,
1327
+ "loss": 1.2629,
1328
+ "mean_token_accuracy": 0.6905880138278008,
1329
+ "num_tokens": 586267.0,
1330
+ "step": 1320
1331
+ },
1332
+ {
1333
+ "entropy": 1.3005138956010343,
1334
+ "epoch": 2.5527831094049906,
1335
+ "grad_norm": 1.4336103200912476,
1336
+ "learning_rate": 1.5435356200527705e-07,
1337
+ "loss": 1.3017,
1338
+ "mean_token_accuracy": 0.6780259110033512,
1339
+ "num_tokens": 590864.0,
1340
+ "step": 1330
1341
+ },
1342
+ {
1343
+ "entropy": 1.2807227730751038,
1344
+ "epoch": 2.5719769673704413,
1345
+ "grad_norm": 1.3677682876586914,
1346
+ "learning_rate": 1.4775725593667547e-07,
1347
+ "loss": 1.2825,
1348
+ "mean_token_accuracy": 0.6882403150200844,
1349
+ "num_tokens": 595215.0,
1350
+ "step": 1340
1351
+ },
1352
+ {
1353
+ "entropy": 1.3279137052595615,
1354
+ "epoch": 2.5911708253358925,
1355
+ "grad_norm": 1.327250599861145,
1356
+ "learning_rate": 1.4116094986807386e-07,
1357
+ "loss": 1.3483,
1358
+ "mean_token_accuracy": 0.6807390071451664,
1359
+ "num_tokens": 599646.0,
1360
+ "step": 1350
1361
+ },
1362
+ {
1363
+ "entropy": 1.2667211405932903,
1364
+ "epoch": 2.6103646833013436,
1365
+ "grad_norm": 1.4356709718704224,
1366
+ "learning_rate": 1.345646437994723e-07,
1367
+ "loss": 1.2679,
1368
+ "mean_token_accuracy": 0.6894605763256549,
1369
+ "num_tokens": 604055.0,
1370
+ "step": 1360
1371
+ },
1372
+ {
1373
+ "entropy": 1.2684335596859455,
1374
+ "epoch": 2.629558541266795,
1375
+ "grad_norm": 1.2923860549926758,
1376
+ "learning_rate": 1.2796833773087072e-07,
1377
+ "loss": 1.2908,
1378
+ "mean_token_accuracy": 0.6826830200850964,
1379
+ "num_tokens": 608366.0,
1380
+ "step": 1370
1381
+ },
1382
+ {
1383
+ "entropy": 1.2696340844035148,
1384
+ "epoch": 2.6487523992322455,
1385
+ "grad_norm": 1.3329826593399048,
1386
+ "learning_rate": 1.2137203166226914e-07,
1387
+ "loss": 1.2539,
1388
+ "mean_token_accuracy": 0.6952502600848675,
1389
+ "num_tokens": 612800.0,
1390
+ "step": 1380
1391
+ },
1392
+ {
1393
+ "entropy": 1.278603233397007,
1394
+ "epoch": 2.6679462571976966,
1395
+ "grad_norm": 1.2472796440124512,
1396
+ "learning_rate": 1.1477572559366754e-07,
1397
+ "loss": 1.2397,
1398
+ "mean_token_accuracy": 0.6929521881043911,
1399
+ "num_tokens": 617190.0,
1400
+ "step": 1390
1401
+ },
1402
+ {
1403
+ "entropy": 1.2521962508559228,
1404
+ "epoch": 2.6871401151631478,
1405
+ "grad_norm": 1.263042688369751,
1406
+ "learning_rate": 1.0817941952506596e-07,
1407
+ "loss": 1.2658,
1408
+ "mean_token_accuracy": 0.6824257783591747,
1409
+ "num_tokens": 621629.0,
1410
+ "step": 1400
1411
+ },
1412
+ {
1413
+ "entropy": 1.2463970981538295,
1414
+ "epoch": 2.706333973128599,
1415
+ "grad_norm": 1.5570292472839355,
1416
+ "learning_rate": 1.0158311345646438e-07,
1417
+ "loss": 1.2261,
1418
+ "mean_token_accuracy": 0.6961454443633557,
1419
+ "num_tokens": 625697.0,
1420
+ "step": 1410
1421
+ },
1422
+ {
1423
+ "entropy": 1.2964108608663083,
1424
+ "epoch": 2.72552783109405,
1425
+ "grad_norm": 1.484802484512329,
1426
+ "learning_rate": 9.498680738786278e-08,
1427
+ "loss": 1.296,
1428
+ "mean_token_accuracy": 0.682018131762743,
1429
+ "num_tokens": 630069.0,
1430
+ "step": 1420
1431
+ },
1432
+ {
1433
+ "entropy": 1.3055186793208122,
1434
+ "epoch": 2.744721689059501,
1435
+ "grad_norm": 1.255502462387085,
1436
+ "learning_rate": 8.839050131926121e-08,
1437
+ "loss": 1.3125,
1438
+ "mean_token_accuracy": 0.676883514970541,
1439
+ "num_tokens": 634623.0,
1440
+ "step": 1430
1441
+ },
1442
+ {
1443
+ "entropy": 1.2824440211057664,
1444
+ "epoch": 2.763915547024952,
1445
+ "grad_norm": 1.4396237134933472,
1446
+ "learning_rate": 8.179419525065963e-08,
1447
+ "loss": 1.2782,
1448
+ "mean_token_accuracy": 0.6812773160636425,
1449
+ "num_tokens": 638785.0,
1450
+ "step": 1440
1451
+ },
1452
+ {
1453
+ "entropy": 1.2704365581274033,
1454
+ "epoch": 2.783109404990403,
1455
+ "grad_norm": 1.401594638824463,
1456
+ "learning_rate": 7.519788918205805e-08,
1457
+ "loss": 1.2688,
1458
+ "mean_token_accuracy": 0.693631474673748,
1459
+ "num_tokens": 643082.0,
1460
+ "step": 1450
1461
+ },
1462
+ {
1463
+ "entropy": 1.252295482158661,
1464
+ "epoch": 2.802303262955854,
1465
+ "grad_norm": 1.3680243492126465,
1466
+ "learning_rate": 6.860158311345645e-08,
1467
+ "loss": 1.2254,
1468
+ "mean_token_accuracy": 0.6942887440323829,
1469
+ "num_tokens": 647322.0,
1470
+ "step": 1460
1471
+ },
1472
+ {
1473
+ "entropy": 1.2678297027945518,
1474
+ "epoch": 2.8214971209213053,
1475
+ "grad_norm": 1.5171517133712769,
1476
+ "learning_rate": 6.200527704485487e-08,
1477
+ "loss": 1.2417,
1478
+ "mean_token_accuracy": 0.6963775165379047,
1479
+ "num_tokens": 651663.0,
1480
+ "step": 1470
1481
+ },
1482
+ {
1483
+ "entropy": 1.2890452943742274,
1484
+ "epoch": 2.840690978886756,
1485
+ "grad_norm": 1.2403157949447632,
1486
+ "learning_rate": 5.540897097625329e-08,
1487
+ "loss": 1.2898,
1488
+ "mean_token_accuracy": 0.6854783184826374,
1489
+ "num_tokens": 656346.0,
1490
+ "step": 1480
1491
+ },
1492
+ {
1493
+ "entropy": 1.3001275762915612,
1494
+ "epoch": 2.859884836852207,
1495
+ "grad_norm": 1.4517172574996948,
1496
+ "learning_rate": 4.8812664907651714e-08,
1497
+ "loss": 1.3287,
1498
+ "mean_token_accuracy": 0.6778113000094891,
1499
+ "num_tokens": 661003.0,
1500
+ "step": 1490
1501
+ },
1502
+ {
1503
+ "entropy": 1.2507057949900626,
1504
+ "epoch": 2.8790786948176583,
1505
+ "grad_norm": 1.2604531049728394,
1506
+ "learning_rate": 4.2216358839050126e-08,
1507
+ "loss": 1.3103,
1508
+ "mean_token_accuracy": 0.6751070104539394,
1509
+ "num_tokens": 665563.0,
1510
+ "step": 1500
1511
+ },
1512
+ {
1513
+ "entropy": 1.2690322190523147,
1514
+ "epoch": 2.8982725527831095,
1515
+ "grad_norm": 1.3388428688049316,
1516
+ "learning_rate": 3.562005277044855e-08,
1517
+ "loss": 1.345,
1518
+ "mean_token_accuracy": 0.6880094990134239,
1519
+ "num_tokens": 670193.0,
1520
+ "step": 1510
1521
+ },
1522
+ {
1523
+ "entropy": 1.2800460867583752,
1524
+ "epoch": 2.9174664107485606,
1525
+ "grad_norm": 1.5586973428726196,
1526
+ "learning_rate": 2.9023746701846965e-08,
1527
+ "loss": 1.345,
1528
+ "mean_token_accuracy": 0.6793852631002665,
1529
+ "num_tokens": 674503.0,
1530
+ "step": 1520
1531
+ },
1532
+ {
1533
+ "entropy": 1.2741929218173027,
1534
+ "epoch": 2.9366602687140118,
1535
+ "grad_norm": 1.383112907409668,
1536
+ "learning_rate": 2.2427440633245383e-08,
1537
+ "loss": 1.2925,
1538
+ "mean_token_accuracy": 0.6897002138197422,
1539
+ "num_tokens": 678932.0,
1540
+ "step": 1530
1541
+ },
1542
+ {
1543
+ "entropy": 1.2852642297744752,
1544
+ "epoch": 2.9558541266794625,
1545
+ "grad_norm": 1.642594575881958,
1546
+ "learning_rate": 1.58311345646438e-08,
1547
+ "loss": 1.2935,
1548
+ "mean_token_accuracy": 0.6824041597545147,
1549
+ "num_tokens": 683365.0,
1550
+ "step": 1540
1551
+ },
1552
+ {
1553
+ "entropy": 1.2600287146866322,
1554
+ "epoch": 2.9750479846449136,
1555
+ "grad_norm": 1.5364669561386108,
1556
+ "learning_rate": 9.234828496042217e-09,
1557
+ "loss": 1.2706,
1558
+ "mean_token_accuracy": 0.6923547603189946,
1559
+ "num_tokens": 687684.0,
1560
+ "step": 1550
1561
+ },
1562
+ {
1563
+ "entropy": 1.2621777415275575,
1564
+ "epoch": 2.9942418426103647,
1565
+ "grad_norm": 1.3073114156723022,
1566
+ "learning_rate": 2.638522427440633e-09,
1567
+ "loss": 1.2944,
1568
+ "mean_token_accuracy": 0.6885419115424156,
1569
+ "num_tokens": 691872.0,
1570
+ "step": 1560
1571
+ }
1572
+ ],
1573
+ "logging_steps": 10,
1574
+ "max_steps": 1563,
1575
+ "num_input_tokens_seen": 0,
1576
+ "num_train_epochs": 3,
1577
+ "save_steps": 500,
1578
+ "stateful_callbacks": {
1579
+ "TrainerControl": {
1580
+ "args": {
1581
+ "should_epoch_stop": false,
1582
+ "should_evaluate": false,
1583
+ "should_log": false,
1584
+ "should_save": true,
1585
+ "should_training_stop": true
1586
+ },
1587
+ "attributes": {}
1588
+ }
1589
+ },
1590
+ "total_flos": 2.814675829088256e+16,
1591
+ "train_batch_size": 1,
1592
+ "trial_name": null,
1593
+ "trial_params": null
1594
+ }
justification-only-lora/checkpoint-1563/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a58e27d7a95a1480fb9af6d6f097ae245d2b6f610a857c664827804e835e1957
3
+ size 6417
justification-only-lora/checkpoint-521/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-2-7b-chat-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:meta-llama/Llama-2-7b-chat-hf
7
+ - lora
8
+ - sft
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
justification-only-lora/checkpoint-521/adapter_config.json ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
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": 128,
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": 64,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "q_proj",
33
+ "k_proj",
34
+ "v_proj",
35
+ "up_proj",
36
+ "o_proj",
37
+ "down_proj",
38
+ "gate_proj"
39
+ ],
40
+ "target_parameters": null,
41
+ "task_type": "CAUSAL_LM",
42
+ "trainable_token_indices": null,
43
+ "use_dora": false,
44
+ "use_qalora": false,
45
+ "use_rslora": false
46
+ }
justification-only-lora/checkpoint-521/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7941bbe2f86985e67b8663d98cd90d4639c637f59df12c6235a7ca51360cf045
3
+ size 639691872
justification-only-lora/checkpoint-521/chat_template.jinja ADDED
@@ -0,0 +1 @@
 
 
1
+ {% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}
justification-only-lora/checkpoint-521/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:87f54761eb964c7d57a91145fb39db62a794aee7ca80c8e1b59ee3e555d91a30
3
+ size 1279641507
justification-only-lora/checkpoint-521/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7d7567a702399b2bb9bdc6084226aa2c5dfd331906b03b06bff478ca0b80bf8c
3
+ size 14645
justification-only-lora/checkpoint-521/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:da78be9f53e992f0a1b40218097fcc6664878153149e04ad89472a4838d0a0f4
3
+ size 1465
justification-only-lora/checkpoint-521/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
justification-only-lora/checkpoint-521/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
justification-only-lora/checkpoint-521/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
justification-only-lora/checkpoint-521/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": null,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": false,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false
43
+ }
justification-only-lora/checkpoint-521/trainer_state.json ADDED
@@ -0,0 +1,554 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.0,
6
+ "eval_steps": 500,
7
+ "global_step": 521,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.5444401994347572,
14
+ "epoch": 0.019193857965451054,
15
+ "grad_norm": 5.821522235870361,
16
+ "learning_rate": 1.9148936170212765e-07,
17
+ "loss": 4.1401,
18
+ "mean_token_accuracy": 0.4060008004307747,
19
+ "num_tokens": 4245.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 1.5042417280375957,
24
+ "epoch": 0.03838771593090211,
25
+ "grad_norm": 5.973490238189697,
26
+ "learning_rate": 4.0425531914893614e-07,
27
+ "loss": 4.0713,
28
+ "mean_token_accuracy": 0.4032037228345871,
29
+ "num_tokens": 8699.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 1.5192734643816947,
34
+ "epoch": 0.05758157389635317,
35
+ "grad_norm": 5.376368999481201,
36
+ "learning_rate": 6.170212765957446e-07,
37
+ "loss": 3.9752,
38
+ "mean_token_accuracy": 0.396929800696671,
39
+ "num_tokens": 13344.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 1.5850717440247535,
44
+ "epoch": 0.07677543186180422,
45
+ "grad_norm": 4.978009223937988,
46
+ "learning_rate": 8.297872340425532e-07,
47
+ "loss": 4.0101,
48
+ "mean_token_accuracy": 0.398511266708374,
49
+ "num_tokens": 17548.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 1.609639537334442,
54
+ "epoch": 0.09596928982725528,
55
+ "grad_norm": 5.168197154998779,
56
+ "learning_rate": 9.986807387862796e-07,
57
+ "loss": 4.0455,
58
+ "mean_token_accuracy": 0.39038523491472005,
59
+ "num_tokens": 21726.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 1.6230455122888088,
64
+ "epoch": 0.11516314779270634,
65
+ "grad_norm": 4.924302577972412,
66
+ "learning_rate": 9.92084432717678e-07,
67
+ "loss": 3.805,
68
+ "mean_token_accuracy": 0.41029399298131464,
69
+ "num_tokens": 26305.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 1.6385258689522744,
74
+ "epoch": 0.1343570057581574,
75
+ "grad_norm": 5.023738861083984,
76
+ "learning_rate": 9.854881266490765e-07,
77
+ "loss": 3.6963,
78
+ "mean_token_accuracy": 0.4034191995859146,
79
+ "num_tokens": 30867.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 1.6791253253817557,
84
+ "epoch": 0.15355086372360843,
85
+ "grad_norm": 4.995085716247559,
86
+ "learning_rate": 9.788918205804749e-07,
87
+ "loss": 3.5687,
88
+ "mean_token_accuracy": 0.41049087755382063,
89
+ "num_tokens": 35488.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 1.7368177756667138,
94
+ "epoch": 0.1727447216890595,
95
+ "grad_norm": 5.233994007110596,
96
+ "learning_rate": 9.722955145118733e-07,
97
+ "loss": 3.502,
98
+ "mean_token_accuracy": 0.41353076659142973,
99
+ "num_tokens": 39905.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 1.7768422558903694,
104
+ "epoch": 0.19193857965451055,
105
+ "grad_norm": 4.299875259399414,
106
+ "learning_rate": 9.656992084432716e-07,
107
+ "loss": 3.4098,
108
+ "mean_token_accuracy": 0.4197281800210476,
109
+ "num_tokens": 44208.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 1.8558007434010506,
114
+ "epoch": 0.21113243761996162,
115
+ "grad_norm": 4.665222644805908,
116
+ "learning_rate": 9.591029023746702e-07,
117
+ "loss": 3.2665,
118
+ "mean_token_accuracy": 0.42318747080862523,
119
+ "num_tokens": 48508.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 1.8271729901432991,
124
+ "epoch": 0.23032629558541268,
125
+ "grad_norm": 3.741534948348999,
126
+ "learning_rate": 9.525065963060686e-07,
127
+ "loss": 3.0302,
128
+ "mean_token_accuracy": 0.4432856226339936,
129
+ "num_tokens": 53006.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 1.855116668343544,
134
+ "epoch": 0.2495201535508637,
135
+ "grad_norm": 3.7163283824920654,
136
+ "learning_rate": 9.459102902374669e-07,
137
+ "loss": 2.9221,
138
+ "mean_token_accuracy": 0.45197133012115953,
139
+ "num_tokens": 57517.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 1.8998430132865907,
144
+ "epoch": 0.2687140115163148,
145
+ "grad_norm": 3.359804153442383,
146
+ "learning_rate": 9.393139841688654e-07,
147
+ "loss": 2.862,
148
+ "mean_token_accuracy": 0.4820567347109318,
149
+ "num_tokens": 61859.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 1.8810108318924903,
154
+ "epoch": 0.28790786948176583,
155
+ "grad_norm": 3.24143648147583,
156
+ "learning_rate": 9.327176781002638e-07,
157
+ "loss": 2.6863,
158
+ "mean_token_accuracy": 0.4882553808391094,
159
+ "num_tokens": 66294.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 1.8664621368050576,
164
+ "epoch": 0.30710172744721687,
165
+ "grad_norm": 3.21515154838562,
166
+ "learning_rate": 9.261213720316622e-07,
167
+ "loss": 2.5571,
168
+ "mean_token_accuracy": 0.4904331646859646,
169
+ "num_tokens": 70881.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 1.9047470435500145,
174
+ "epoch": 0.32629558541266795,
175
+ "grad_norm": 2.9383370876312256,
176
+ "learning_rate": 9.195250659630607e-07,
177
+ "loss": 2.4253,
178
+ "mean_token_accuracy": 0.5186557050794363,
179
+ "num_tokens": 75343.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 1.8957982853055,
184
+ "epoch": 0.345489443378119,
185
+ "grad_norm": 2.855672836303711,
186
+ "learning_rate": 9.129287598944591e-07,
187
+ "loss": 2.3765,
188
+ "mean_token_accuracy": 0.5165872510522604,
189
+ "num_tokens": 79813.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 1.8749225288629532,
194
+ "epoch": 0.3646833013435701,
195
+ "grad_norm": 2.4022603034973145,
196
+ "learning_rate": 9.063324538258574e-07,
197
+ "loss": 2.262,
198
+ "mean_token_accuracy": 0.5304524928331376,
199
+ "num_tokens": 84432.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 1.859298901259899,
204
+ "epoch": 0.3838771593090211,
205
+ "grad_norm": 2.477881908416748,
206
+ "learning_rate": 8.997361477572559e-07,
207
+ "loss": 2.1756,
208
+ "mean_token_accuracy": 0.5431556064635515,
209
+ "num_tokens": 88923.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 1.8629574179649353,
214
+ "epoch": 0.40307101727447214,
215
+ "grad_norm": 2.1476128101348877,
216
+ "learning_rate": 8.931398416886543e-07,
217
+ "loss": 2.1339,
218
+ "mean_token_accuracy": 0.5666973438113928,
219
+ "num_tokens": 93328.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 1.8807074934244157,
224
+ "epoch": 0.42226487523992323,
225
+ "grad_norm": 2.3548238277435303,
226
+ "learning_rate": 8.865435356200526e-07,
227
+ "loss": 2.0982,
228
+ "mean_token_accuracy": 0.5757683675736189,
229
+ "num_tokens": 97899.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 1.9242157697677613,
234
+ "epoch": 0.44145873320537427,
235
+ "grad_norm": 2.224064588546753,
236
+ "learning_rate": 8.799472295514512e-07,
237
+ "loss": 2.0095,
238
+ "mean_token_accuracy": 0.5813840452581645,
239
+ "num_tokens": 102067.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 1.8383784875273705,
244
+ "epoch": 0.46065259117082535,
245
+ "grad_norm": 2.35628604888916,
246
+ "learning_rate": 8.733509234828496e-07,
247
+ "loss": 2.0116,
248
+ "mean_token_accuracy": 0.582221444323659,
249
+ "num_tokens": 106474.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 1.8541715443134308,
254
+ "epoch": 0.4798464491362764,
255
+ "grad_norm": 2.1513049602508545,
256
+ "learning_rate": 8.667546174142479e-07,
257
+ "loss": 1.9723,
258
+ "mean_token_accuracy": 0.591744914278388,
259
+ "num_tokens": 110847.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 1.8240503028035164,
264
+ "epoch": 0.4990403071017274,
265
+ "grad_norm": 1.9908933639526367,
266
+ "learning_rate": 8.601583113456464e-07,
267
+ "loss": 1.9192,
268
+ "mean_token_accuracy": 0.583719938248396,
269
+ "num_tokens": 115237.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 1.8065304696559905,
274
+ "epoch": 0.5182341650671785,
275
+ "grad_norm": 2.1833651065826416,
276
+ "learning_rate": 8.535620052770448e-07,
277
+ "loss": 1.8791,
278
+ "mean_token_accuracy": 0.5988160844892263,
279
+ "num_tokens": 119549.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 1.7882312104105949,
284
+ "epoch": 0.5374280230326296,
285
+ "grad_norm": 2.280733823776245,
286
+ "learning_rate": 8.469656992084431e-07,
287
+ "loss": 1.899,
288
+ "mean_token_accuracy": 0.5769031669944524,
289
+ "num_tokens": 123989.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 1.7919606953859328,
294
+ "epoch": 0.5566218809980806,
295
+ "grad_norm": 2.1053104400634766,
296
+ "learning_rate": 8.403693931398417e-07,
297
+ "loss": 1.833,
298
+ "mean_token_accuracy": 0.5953757733106613,
299
+ "num_tokens": 128278.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 1.8032251179218293,
304
+ "epoch": 0.5758157389635317,
305
+ "grad_norm": 2.0865530967712402,
306
+ "learning_rate": 8.337730870712401e-07,
307
+ "loss": 1.8991,
308
+ "mean_token_accuracy": 0.5826169475913048,
309
+ "num_tokens": 133078.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 1.7583968698978425,
314
+ "epoch": 0.5950095969289827,
315
+ "grad_norm": 1.7579165697097778,
316
+ "learning_rate": 8.271767810026385e-07,
317
+ "loss": 1.7885,
318
+ "mean_token_accuracy": 0.6143867563456297,
319
+ "num_tokens": 137541.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 1.7979290679097175,
324
+ "epoch": 0.6142034548944337,
325
+ "grad_norm": 1.8130688667297363,
326
+ "learning_rate": 8.205804749340369e-07,
327
+ "loss": 1.8252,
328
+ "mean_token_accuracy": 0.6005033150315284,
329
+ "num_tokens": 141810.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 1.7790041908621788,
334
+ "epoch": 0.6333973128598849,
335
+ "grad_norm": 1.9245020151138306,
336
+ "learning_rate": 8.139841688654353e-07,
337
+ "loss": 1.7798,
338
+ "mean_token_accuracy": 0.613793533295393,
339
+ "num_tokens": 146112.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 1.7689658552408218,
344
+ "epoch": 0.6525911708253359,
345
+ "grad_norm": 2.208102226257324,
346
+ "learning_rate": 8.073878627968337e-07,
347
+ "loss": 1.7584,
348
+ "mean_token_accuracy": 0.5983480997383595,
349
+ "num_tokens": 150609.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 1.7603006795048715,
354
+ "epoch": 0.6717850287907869,
355
+ "grad_norm": 1.8552649021148682,
356
+ "learning_rate": 8.007915567282322e-07,
357
+ "loss": 1.7016,
358
+ "mean_token_accuracy": 0.6168740216642619,
359
+ "num_tokens": 155088.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 1.741025310754776,
364
+ "epoch": 0.690978886756238,
365
+ "grad_norm": 1.9795598983764648,
366
+ "learning_rate": 7.941952506596306e-07,
367
+ "loss": 1.7031,
368
+ "mean_token_accuracy": 0.6189993746578694,
369
+ "num_tokens": 159495.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 1.763644915819168,
374
+ "epoch": 0.710172744721689,
375
+ "grad_norm": 2.2528767585754395,
376
+ "learning_rate": 7.87598944591029e-07,
377
+ "loss": 1.6961,
378
+ "mean_token_accuracy": 0.6185917239636183,
379
+ "num_tokens": 163793.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 1.739506982266903,
384
+ "epoch": 0.7293666026871402,
385
+ "grad_norm": 1.9315766096115112,
386
+ "learning_rate": 7.810026385224274e-07,
387
+ "loss": 1.6339,
388
+ "mean_token_accuracy": 0.6323129627853632,
389
+ "num_tokens": 168268.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 1.7659575924277306,
394
+ "epoch": 0.7485604606525912,
395
+ "grad_norm": 1.8060170412063599,
396
+ "learning_rate": 7.744063324538258e-07,
397
+ "loss": 1.6461,
398
+ "mean_token_accuracy": 0.6334325969219208,
399
+ "num_tokens": 172612.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 1.7049371361732484,
404
+ "epoch": 0.7677543186180422,
405
+ "grad_norm": 1.7351154088974,
406
+ "learning_rate": 7.678100263852242e-07,
407
+ "loss": 1.5584,
408
+ "mean_token_accuracy": 0.64255366101861,
409
+ "num_tokens": 176987.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 1.6969178169965744,
414
+ "epoch": 0.7869481765834933,
415
+ "grad_norm": 1.5524696111679077,
416
+ "learning_rate": 7.612137203166226e-07,
417
+ "loss": 1.6435,
418
+ "mean_token_accuracy": 0.632745499163866,
419
+ "num_tokens": 181538.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 1.6801453217864037,
424
+ "epoch": 0.8061420345489443,
425
+ "grad_norm": 1.667938470840454,
426
+ "learning_rate": 7.546174142480211e-07,
427
+ "loss": 1.5851,
428
+ "mean_token_accuracy": 0.6391880080103874,
429
+ "num_tokens": 185819.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 1.6663354828953743,
434
+ "epoch": 0.8253358925143954,
435
+ "grad_norm": 1.5086743831634521,
436
+ "learning_rate": 7.480211081794196e-07,
437
+ "loss": 1.5759,
438
+ "mean_token_accuracy": 0.6453739482909441,
439
+ "num_tokens": 190254.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 1.6495836034417153,
444
+ "epoch": 0.8445297504798465,
445
+ "grad_norm": 1.7330267429351807,
446
+ "learning_rate": 7.414248021108179e-07,
447
+ "loss": 1.5403,
448
+ "mean_token_accuracy": 0.6486042737960815,
449
+ "num_tokens": 194643.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 1.6953262895345689,
454
+ "epoch": 0.8637236084452975,
455
+ "grad_norm": 1.465407133102417,
456
+ "learning_rate": 7.348284960422163e-07,
457
+ "loss": 1.5757,
458
+ "mean_token_accuracy": 0.6440861701965332,
459
+ "num_tokens": 198983.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 1.6009652018547058,
464
+ "epoch": 0.8829174664107485,
465
+ "grad_norm": 1.484931230545044,
466
+ "learning_rate": 7.282321899736148e-07,
467
+ "loss": 1.4547,
468
+ "mean_token_accuracy": 0.6605511672794819,
469
+ "num_tokens": 203270.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 1.6046269670128823,
474
+ "epoch": 0.9021113243761996,
475
+ "grad_norm": 1.4576069116592407,
476
+ "learning_rate": 7.216358839050131e-07,
477
+ "loss": 1.5508,
478
+ "mean_token_accuracy": 0.6439322311431169,
479
+ "num_tokens": 207696.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 1.6068053118884564,
484
+ "epoch": 0.9213051823416507,
485
+ "grad_norm": 1.7096375226974487,
486
+ "learning_rate": 7.150395778364116e-07,
487
+ "loss": 1.5665,
488
+ "mean_token_accuracy": 0.6389439355581998,
489
+ "num_tokens": 212574.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 1.58553556650877,
494
+ "epoch": 0.9404990403071017,
495
+ "grad_norm": 1.8892183303833008,
496
+ "learning_rate": 7.084432717678101e-07,
497
+ "loss": 1.5476,
498
+ "mean_token_accuracy": 0.6533854089677333,
499
+ "num_tokens": 217308.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 1.6013462141156196,
504
+ "epoch": 0.9596928982725528,
505
+ "grad_norm": 1.3890715837478638,
506
+ "learning_rate": 7.018469656992084e-07,
507
+ "loss": 1.5067,
508
+ "mean_token_accuracy": 0.6439886368811131,
509
+ "num_tokens": 221638.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 1.5622883230447768,
514
+ "epoch": 0.9788867562380038,
515
+ "grad_norm": 1.4576449394226074,
516
+ "learning_rate": 6.952506596306068e-07,
517
+ "loss": 1.5282,
518
+ "mean_token_accuracy": 0.6542089767754078,
519
+ "num_tokens": 226264.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 1.5611482337117195,
524
+ "epoch": 0.9980806142034548,
525
+ "grad_norm": 1.3677759170532227,
526
+ "learning_rate": 6.886543535620053e-07,
527
+ "loss": 1.4478,
528
+ "mean_token_accuracy": 0.6510695222765207,
529
+ "num_tokens": 230675.0,
530
+ "step": 520
531
+ }
532
+ ],
533
+ "logging_steps": 10,
534
+ "max_steps": 1563,
535
+ "num_input_tokens_seen": 0,
536
+ "num_train_epochs": 3,
537
+ "save_steps": 500,
538
+ "stateful_callbacks": {
539
+ "TrainerControl": {
540
+ "args": {
541
+ "should_epoch_stop": false,
542
+ "should_evaluate": false,
543
+ "should_log": false,
544
+ "should_save": true,
545
+ "should_training_stop": false
546
+ },
547
+ "attributes": {}
548
+ }
549
+ },
550
+ "total_flos": 9382252763627520.0,
551
+ "train_batch_size": 1,
552
+ "trial_name": null,
553
+ "trial_params": null
554
+ }
justification-only-lora/checkpoint-521/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a58e27d7a95a1480fb9af6d6f097ae245d2b6f610a857c664827804e835e1957
3
+ size 6417
justification-only-lora/run_config.json ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
3
+ "num_train_epochs": 3.0,
4
+ "learning_rate": 1e-06,
5
+ "full_finetune": false,
6
+ "use_qlora": false,
7
+ "lora_r": 64,
8
+ "dataset": "HarethahMo/extended-refusal",
9
+ "max_steps": null,
10
+ "response_aspect": "justification_only",
11
+ "train_examples": 4168,
12
+ "assistant_only_loss": false
13
+ }
justification-only-lora/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
justification-only-lora/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
justification-only-lora/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
justification-only-lora/tokenizer_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": null,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": false,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false
43
+ }
justification-only-lora/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a58e27d7a95a1480fb9af6d6f097ae245d2b6f610a857c664827804e835e1957
3
+ size 6417