gagan3012 commited on
Commit
0af2b68
1 Parent(s): 7662d5e

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. README.md +55 -0
  2. checkpoint-100/README.md +204 -0
  3. checkpoint-100/adapter_config.json +32 -0
  4. checkpoint-100/adapter_model.safetensors +3 -0
  5. checkpoint-100/optimizer.pt +3 -0
  6. checkpoint-100/pytorch_model.bin +3 -0
  7. checkpoint-100/rng_state.pth +3 -0
  8. checkpoint-100/scheduler.pt +3 -0
  9. checkpoint-100/special_tokens_map.json +24 -0
  10. checkpoint-100/tokenizer.json +0 -0
  11. checkpoint-100/tokenizer.model +3 -0
  12. checkpoint-100/tokenizer_config.json +44 -0
  13. checkpoint-100/trainer_state.json +629 -0
  14. checkpoint-100/training_args.bin +3 -0
  15. checkpoint-1000/README.md +204 -0
  16. checkpoint-1000/adapter_config.json +32 -0
  17. checkpoint-1000/adapter_model.safetensors +3 -0
  18. checkpoint-1000/optimizer.pt +3 -0
  19. checkpoint-1000/pytorch_model.bin +3 -0
  20. checkpoint-1000/rng_state.pth +3 -0
  21. checkpoint-1000/scheduler.pt +3 -0
  22. checkpoint-1000/special_tokens_map.json +24 -0
  23. checkpoint-1000/tokenizer.json +0 -0
  24. checkpoint-1000/tokenizer.model +3 -0
  25. checkpoint-1000/tokenizer_config.json +44 -0
  26. checkpoint-1000/trainer_state.json +0 -0
  27. checkpoint-1000/training_args.bin +3 -0
  28. checkpoint-1100/README.md +204 -0
  29. checkpoint-1100/adapter_config.json +32 -0
  30. checkpoint-1100/adapter_model.safetensors +3 -0
  31. checkpoint-1100/optimizer.pt +3 -0
  32. checkpoint-1100/pytorch_model.bin +3 -0
  33. checkpoint-1100/rng_state.pth +3 -0
  34. checkpoint-1100/scheduler.pt +3 -0
  35. checkpoint-1100/special_tokens_map.json +24 -0
  36. checkpoint-1100/tokenizer.json +0 -0
  37. checkpoint-1100/tokenizer.model +3 -0
  38. checkpoint-1100/tokenizer_config.json +44 -0
  39. checkpoint-1100/trainer_state.json +0 -0
  40. checkpoint-1100/training_args.bin +3 -0
  41. checkpoint-1200/README.md +204 -0
  42. checkpoint-1200/adapter_config.json +32 -0
  43. checkpoint-1200/adapter_model.safetensors +3 -0
  44. checkpoint-1200/optimizer.pt +3 -0
  45. checkpoint-1200/pytorch_model.bin +3 -0
  46. checkpoint-1200/rng_state.pth +3 -0
  47. checkpoint-1200/scheduler.pt +3 -0
  48. checkpoint-1200/special_tokens_map.json +24 -0
  49. checkpoint-1200/tokenizer.json +0 -0
  50. checkpoint-1200/tokenizer.model +3 -0
README.md ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - en
4
+ license: apache-2.0
5
+ tags:
6
+ - mistral
7
+ - Zenith-7B
8
+ pipeline_tag: text-generation
9
+ ---
10
+ # Model Card for Zenith-7B
11
+
12
+ Mistral-7B-v0.1 model fine-tuned on the Ultrafeedback dataset using techinques shown in the paper [Self-Rewarding Language Models](https://arxiv.org/abs/2401.10020).
13
+
14
+ ## Instruction format
15
+
16
+ In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id.
17
+
18
+ E.g.
19
+ ```
20
+ text = "<s>[INST] What is your favourite condiment? [/INST]"
21
+ "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s> "
22
+ "[INST] Do you have mayonnaise recipes? [/INST]"
23
+ ```
24
+
25
+ This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
26
+
27
+ ```python
28
+ from transformers import AutoModelForCausalLM, AutoTokenizer
29
+
30
+ device = "cuda" # the device to load the model onto
31
+
32
+ model = AutoModelForCausalLM.from_pretrained("Xenon1/Zenith-7B")
33
+ tokenizer = AutoTokenizer.from_pretrained("Xenon1/Zenith-7B")
34
+
35
+ messages = [
36
+ {"role": "user", "content": "What is your favourite condiment?"},
37
+ {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
38
+ {"role": "user", "content": "Do you have mayonnaise recipes?"}
39
+ ]
40
+
41
+ encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
42
+
43
+ model_inputs = encodeds.to(device)
44
+ model.to(device)
45
+
46
+ generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
47
+ decoded = tokenizer.batch_decode(generated_ids)
48
+ print(decoded[0])
49
+ ```
50
+
51
+ ## Model Architecture
52
+ This instruction model is based on Mistral-7B-v0.1, a transformer model with the following architecture choices:
53
+ - Grouped-Query Attention
54
+ - Sliding-Window Attention
55
+ - Byte-fallback BPE tokenizer
checkpoint-100/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
checkpoint-100/adapter_config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "up_proj",
23
+ "v_proj",
24
+ "k_proj",
25
+ "o_proj",
26
+ "q_proj",
27
+ "gate_proj",
28
+ "down_proj"
29
+ ],
30
+ "task_type": "CAUSAL_LM",
31
+ "use_rslora": false
32
+ }
checkpoint-100/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:03c7e072a09d82fe41335b1e16e30b2cfdb9e52012e88b0b366aa9fc19b704e9
3
+ size 167832240
checkpoint-100/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7109d45182ade72fd34fd57da343292046385f4c99779d21702f16bec05e961b
3
+ size 335812858
checkpoint-100/pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:049c26b844b79121ddd8379f7f69194e63f6fbf6aa007eeac0c66f17eebb8893
3
+ size 888
checkpoint-100/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c56dcce6c13c6de889d4aae7dc0f064812110912b08fde202e8fc80f391303a4
3
+ size 14244
checkpoint-100/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:003e9a806b828de9b8637858af5bbdebcad9d4b8696a1a67b444bd1986516b15
3
+ size 1064
checkpoint-100/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
+ }
checkpoint-100/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-100/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
checkpoint-100/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": true,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [],
31
+ "bos_token": "<s>",
32
+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
33
+ "clean_up_tokenization_spaces": false,
34
+ "eos_token": "</s>",
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "spaces_between_special_tokens": false,
41
+ "tokenizer_class": "LlamaTokenizer",
42
+ "unk_token": "<unk>",
43
+ "use_default_system_prompt": false
44
+ }
checkpoint-100/trainer_state.json ADDED
@@ -0,0 +1,629 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 0.043094160741219564,
5
+ "eval_steps": 100,
6
+ "global_step": 100,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.0,
13
+ "learning_rate": 5e-05,
14
+ "loss": 1.5475,
15
+ "step": 1
16
+ },
17
+ {
18
+ "epoch": 0.0,
19
+ "learning_rate": 4.999997705921923e-05,
20
+ "loss": 1.4738,
21
+ "step": 2
22
+ },
23
+ {
24
+ "epoch": 0.0,
25
+ "learning_rate": 4.9999908236919016e-05,
26
+ "loss": 1.709,
27
+ "step": 3
28
+ },
29
+ {
30
+ "epoch": 0.0,
31
+ "learning_rate": 4.999979353322567e-05,
32
+ "loss": 1.3682,
33
+ "step": 4
34
+ },
35
+ {
36
+ "epoch": 0.0,
37
+ "learning_rate": 4.99996329483497e-05,
38
+ "loss": 1.4525,
39
+ "step": 5
40
+ },
41
+ {
42
+ "epoch": 0.0,
43
+ "learning_rate": 4.999942648258581e-05,
44
+ "loss": 1.2902,
45
+ "step": 6
46
+ },
47
+ {
48
+ "epoch": 0.0,
49
+ "learning_rate": 4.999917413631294e-05,
50
+ "loss": 1.2581,
51
+ "step": 7
52
+ },
53
+ {
54
+ "epoch": 0.0,
55
+ "learning_rate": 4.9998875909994206e-05,
56
+ "loss": 1.1363,
57
+ "step": 8
58
+ },
59
+ {
60
+ "epoch": 0.0,
61
+ "learning_rate": 4.9998531804176926e-05,
62
+ "loss": 1.0479,
63
+ "step": 9
64
+ },
65
+ {
66
+ "epoch": 0.0,
67
+ "learning_rate": 4.999814181949263e-05,
68
+ "loss": 1.0362,
69
+ "step": 10
70
+ },
71
+ {
72
+ "epoch": 0.0,
73
+ "learning_rate": 4.999770595665704e-05,
74
+ "loss": 0.9415,
75
+ "step": 11
76
+ },
77
+ {
78
+ "epoch": 0.01,
79
+ "learning_rate": 4.999722421647006e-05,
80
+ "loss": 1.0849,
81
+ "step": 12
82
+ },
83
+ {
84
+ "epoch": 0.01,
85
+ "learning_rate": 4.999669659981584e-05,
86
+ "loss": 0.8538,
87
+ "step": 13
88
+ },
89
+ {
90
+ "epoch": 0.01,
91
+ "learning_rate": 4.999612310766268e-05,
92
+ "loss": 0.9404,
93
+ "step": 14
94
+ },
95
+ {
96
+ "epoch": 0.01,
97
+ "learning_rate": 4.9995503741063096e-05,
98
+ "loss": 0.9645,
99
+ "step": 15
100
+ },
101
+ {
102
+ "epoch": 0.01,
103
+ "learning_rate": 4.999483850115379e-05,
104
+ "loss": 1.0898,
105
+ "step": 16
106
+ },
107
+ {
108
+ "epoch": 0.01,
109
+ "learning_rate": 4.9994127389155623e-05,
110
+ "loss": 0.9545,
111
+ "step": 17
112
+ },
113
+ {
114
+ "epoch": 0.01,
115
+ "learning_rate": 4.9993370406373705e-05,
116
+ "loss": 0.8432,
117
+ "step": 18
118
+ },
119
+ {
120
+ "epoch": 0.01,
121
+ "learning_rate": 4.999256755419729e-05,
122
+ "loss": 0.9946,
123
+ "step": 19
124
+ },
125
+ {
126
+ "epoch": 0.01,
127
+ "learning_rate": 4.999171883409982e-05,
128
+ "loss": 0.7908,
129
+ "step": 20
130
+ },
131
+ {
132
+ "epoch": 0.01,
133
+ "learning_rate": 4.999082424763891e-05,
134
+ "loss": 0.8971,
135
+ "step": 21
136
+ },
137
+ {
138
+ "epoch": 0.01,
139
+ "learning_rate": 4.998988379645638e-05,
140
+ "loss": 0.85,
141
+ "step": 22
142
+ },
143
+ {
144
+ "epoch": 0.01,
145
+ "learning_rate": 4.998889748227819e-05,
146
+ "loss": 0.8626,
147
+ "step": 23
148
+ },
149
+ {
150
+ "epoch": 0.01,
151
+ "learning_rate": 4.9987865306914495e-05,
152
+ "loss": 0.8335,
153
+ "step": 24
154
+ },
155
+ {
156
+ "epoch": 0.01,
157
+ "learning_rate": 4.9986787272259596e-05,
158
+ "loss": 0.9314,
159
+ "step": 25
160
+ },
161
+ {
162
+ "epoch": 0.01,
163
+ "learning_rate": 4.998566338029198e-05,
164
+ "loss": 0.8645,
165
+ "step": 26
166
+ },
167
+ {
168
+ "epoch": 0.01,
169
+ "learning_rate": 4.998449363307428e-05,
170
+ "loss": 0.9316,
171
+ "step": 27
172
+ },
173
+ {
174
+ "epoch": 0.01,
175
+ "learning_rate": 4.998327803275328e-05,
176
+ "loss": 0.805,
177
+ "step": 28
178
+ },
179
+ {
180
+ "epoch": 0.01,
181
+ "learning_rate": 4.998201658155994e-05,
182
+ "loss": 1.0418,
183
+ "step": 29
184
+ },
185
+ {
186
+ "epoch": 0.01,
187
+ "learning_rate": 4.998070928180935e-05,
188
+ "loss": 0.649,
189
+ "step": 30
190
+ },
191
+ {
192
+ "epoch": 0.01,
193
+ "learning_rate": 4.997935613590075e-05,
194
+ "loss": 0.8,
195
+ "step": 31
196
+ },
197
+ {
198
+ "epoch": 0.01,
199
+ "learning_rate": 4.997795714631751e-05,
200
+ "loss": 0.8014,
201
+ "step": 32
202
+ },
203
+ {
204
+ "epoch": 0.01,
205
+ "learning_rate": 4.997651231562715e-05,
206
+ "loss": 0.7854,
207
+ "step": 33
208
+ },
209
+ {
210
+ "epoch": 0.01,
211
+ "learning_rate": 4.9975021646481315e-05,
212
+ "loss": 0.8782,
213
+ "step": 34
214
+ },
215
+ {
216
+ "epoch": 0.02,
217
+ "learning_rate": 4.997348514161576e-05,
218
+ "loss": 0.7564,
219
+ "step": 35
220
+ },
221
+ {
222
+ "epoch": 0.02,
223
+ "learning_rate": 4.997190280385039e-05,
224
+ "loss": 0.9438,
225
+ "step": 36
226
+ },
227
+ {
228
+ "epoch": 0.02,
229
+ "learning_rate": 4.997027463608921e-05,
230
+ "loss": 0.9248,
231
+ "step": 37
232
+ },
233
+ {
234
+ "epoch": 0.02,
235
+ "learning_rate": 4.996860064132033e-05,
236
+ "loss": 0.76,
237
+ "step": 38
238
+ },
239
+ {
240
+ "epoch": 0.02,
241
+ "learning_rate": 4.9966880822615965e-05,
242
+ "loss": 0.8834,
243
+ "step": 39
244
+ },
245
+ {
246
+ "epoch": 0.02,
247
+ "learning_rate": 4.996511518313244e-05,
248
+ "loss": 0.8928,
249
+ "step": 40
250
+ },
251
+ {
252
+ "epoch": 0.02,
253
+ "learning_rate": 4.996330372611017e-05,
254
+ "loss": 0.8857,
255
+ "step": 41
256
+ },
257
+ {
258
+ "epoch": 0.02,
259
+ "learning_rate": 4.996144645487364e-05,
260
+ "loss": 0.7975,
261
+ "step": 42
262
+ },
263
+ {
264
+ "epoch": 0.02,
265
+ "learning_rate": 4.995954337283145e-05,
266
+ "loss": 0.7815,
267
+ "step": 43
268
+ },
269
+ {
270
+ "epoch": 0.02,
271
+ "learning_rate": 4.9957594483476236e-05,
272
+ "loss": 0.8869,
273
+ "step": 44
274
+ },
275
+ {
276
+ "epoch": 0.02,
277
+ "learning_rate": 4.995559979038474e-05,
278
+ "loss": 0.9173,
279
+ "step": 45
280
+ },
281
+ {
282
+ "epoch": 0.02,
283
+ "learning_rate": 4.995355929721773e-05,
284
+ "loss": 0.9258,
285
+ "step": 46
286
+ },
287
+ {
288
+ "epoch": 0.02,
289
+ "learning_rate": 4.995147300772006e-05,
290
+ "loss": 0.896,
291
+ "step": 47
292
+ },
293
+ {
294
+ "epoch": 0.02,
295
+ "learning_rate": 4.994934092572061e-05,
296
+ "loss": 0.893,
297
+ "step": 48
298
+ },
299
+ {
300
+ "epoch": 0.02,
301
+ "learning_rate": 4.994716305513232e-05,
302
+ "loss": 0.8257,
303
+ "step": 49
304
+ },
305
+ {
306
+ "epoch": 0.02,
307
+ "learning_rate": 4.994493939995214e-05,
308
+ "loss": 0.8759,
309
+ "step": 50
310
+ },
311
+ {
312
+ "epoch": 0.02,
313
+ "learning_rate": 4.994266996426107e-05,
314
+ "loss": 0.9216,
315
+ "step": 51
316
+ },
317
+ {
318
+ "epoch": 0.02,
319
+ "learning_rate": 4.994035475222412e-05,
320
+ "loss": 0.9097,
321
+ "step": 52
322
+ },
323
+ {
324
+ "epoch": 0.02,
325
+ "learning_rate": 4.9937993768090306e-05,
326
+ "loss": 1.015,
327
+ "step": 53
328
+ },
329
+ {
330
+ "epoch": 0.02,
331
+ "learning_rate": 4.993558701619266e-05,
332
+ "loss": 0.8633,
333
+ "step": 54
334
+ },
335
+ {
336
+ "epoch": 0.02,
337
+ "learning_rate": 4.9933134500948205e-05,
338
+ "loss": 0.928,
339
+ "step": 55
340
+ },
341
+ {
342
+ "epoch": 0.02,
343
+ "learning_rate": 4.993063622685794e-05,
344
+ "loss": 0.8069,
345
+ "step": 56
346
+ },
347
+ {
348
+ "epoch": 0.02,
349
+ "learning_rate": 4.9928092198506866e-05,
350
+ "loss": 0.885,
351
+ "step": 57
352
+ },
353
+ {
354
+ "epoch": 0.02,
355
+ "learning_rate": 4.992550242056393e-05,
356
+ "loss": 0.7342,
357
+ "step": 58
358
+ },
359
+ {
360
+ "epoch": 0.03,
361
+ "learning_rate": 4.992286689778207e-05,
362
+ "loss": 0.8593,
363
+ "step": 59
364
+ },
365
+ {
366
+ "epoch": 0.03,
367
+ "learning_rate": 4.992018563499814e-05,
368
+ "loss": 0.9458,
369
+ "step": 60
370
+ },
371
+ {
372
+ "epoch": 0.03,
373
+ "learning_rate": 4.991745863713299e-05,
374
+ "loss": 0.9511,
375
+ "step": 61
376
+ },
377
+ {
378
+ "epoch": 0.03,
379
+ "learning_rate": 4.991468590919135e-05,
380
+ "loss": 0.8605,
381
+ "step": 62
382
+ },
383
+ {
384
+ "epoch": 0.03,
385
+ "learning_rate": 4.9911867456261916e-05,
386
+ "loss": 0.76,
387
+ "step": 63
388
+ },
389
+ {
390
+ "epoch": 0.03,
391
+ "learning_rate": 4.9909003283517283e-05,
392
+ "loss": 0.8037,
393
+ "step": 64
394
+ },
395
+ {
396
+ "epoch": 0.03,
397
+ "learning_rate": 4.990609339621397e-05,
398
+ "loss": 0.8945,
399
+ "step": 65
400
+ },
401
+ {
402
+ "epoch": 0.03,
403
+ "learning_rate": 4.990313779969237e-05,
404
+ "loss": 0.7774,
405
+ "step": 66
406
+ },
407
+ {
408
+ "epoch": 0.03,
409
+ "learning_rate": 4.990013649937679e-05,
410
+ "loss": 0.8737,
411
+ "step": 67
412
+ },
413
+ {
414
+ "epoch": 0.03,
415
+ "learning_rate": 4.989708950077541e-05,
416
+ "loss": 0.8914,
417
+ "step": 68
418
+ },
419
+ {
420
+ "epoch": 0.03,
421
+ "learning_rate": 4.9893996809480246e-05,
422
+ "loss": 0.8682,
423
+ "step": 69
424
+ },
425
+ {
426
+ "epoch": 0.03,
427
+ "learning_rate": 4.9890858431167226e-05,
428
+ "loss": 0.7745,
429
+ "step": 70
430
+ },
431
+ {
432
+ "epoch": 0.03,
433
+ "learning_rate": 4.988767437159608e-05,
434
+ "loss": 1.0306,
435
+ "step": 71
436
+ },
437
+ {
438
+ "epoch": 0.03,
439
+ "learning_rate": 4.988444463661041e-05,
440
+ "loss": 0.904,
441
+ "step": 72
442
+ },
443
+ {
444
+ "epoch": 0.03,
445
+ "learning_rate": 4.98811692321376e-05,
446
+ "loss": 0.8478,
447
+ "step": 73
448
+ },
449
+ {
450
+ "epoch": 0.03,
451
+ "learning_rate": 4.9877848164188904e-05,
452
+ "loss": 0.7117,
453
+ "step": 74
454
+ },
455
+ {
456
+ "epoch": 0.03,
457
+ "learning_rate": 4.987448143885933e-05,
458
+ "loss": 0.6789,
459
+ "step": 75
460
+ },
461
+ {
462
+ "epoch": 0.03,
463
+ "learning_rate": 4.987106906232773e-05,
464
+ "loss": 0.9385,
465
+ "step": 76
466
+ },
467
+ {
468
+ "epoch": 0.03,
469
+ "learning_rate": 4.9867611040856695e-05,
470
+ "loss": 1.049,
471
+ "step": 77
472
+ },
473
+ {
474
+ "epoch": 0.03,
475
+ "learning_rate": 4.9864107380792594e-05,
476
+ "loss": 0.8914,
477
+ "step": 78
478
+ },
479
+ {
480
+ "epoch": 0.03,
481
+ "learning_rate": 4.986055808856558e-05,
482
+ "loss": 0.8211,
483
+ "step": 79
484
+ },
485
+ {
486
+ "epoch": 0.03,
487
+ "learning_rate": 4.9856963170689525e-05,
488
+ "loss": 0.9007,
489
+ "step": 80
490
+ },
491
+ {
492
+ "epoch": 0.03,
493
+ "learning_rate": 4.9853322633762045e-05,
494
+ "loss": 0.832,
495
+ "step": 81
496
+ },
497
+ {
498
+ "epoch": 0.04,
499
+ "learning_rate": 4.984963648446449e-05,
500
+ "loss": 0.807,
501
+ "step": 82
502
+ },
503
+ {
504
+ "epoch": 0.04,
505
+ "learning_rate": 4.984590472956191e-05,
506
+ "loss": 0.7031,
507
+ "step": 83
508
+ },
509
+ {
510
+ "epoch": 0.04,
511
+ "learning_rate": 4.984212737590304e-05,
512
+ "loss": 0.9261,
513
+ "step": 84
514
+ },
515
+ {
516
+ "epoch": 0.04,
517
+ "learning_rate": 4.983830443042033e-05,
518
+ "loss": 0.7759,
519
+ "step": 85
520
+ },
521
+ {
522
+ "epoch": 0.04,
523
+ "learning_rate": 4.983443590012989e-05,
524
+ "loss": 0.7147,
525
+ "step": 86
526
+ },
527
+ {
528
+ "epoch": 0.04,
529
+ "learning_rate": 4.9830521792131484e-05,
530
+ "loss": 0.8554,
531
+ "step": 87
532
+ },
533
+ {
534
+ "epoch": 0.04,
535
+ "learning_rate": 4.982656211360852e-05,
536
+ "loss": 0.8052,
537
+ "step": 88
538
+ },
539
+ {
540
+ "epoch": 0.04,
541
+ "learning_rate": 4.982255687182806e-05,
542
+ "loss": 0.8408,
543
+ "step": 89
544
+ },
545
+ {
546
+ "epoch": 0.04,
547
+ "learning_rate": 4.981850607414077e-05,
548
+ "loss": 0.7086,
549
+ "step": 90
550
+ },
551
+ {
552
+ "epoch": 0.04,
553
+ "learning_rate": 4.981440972798092e-05,
554
+ "loss": 0.7808,
555
+ "step": 91
556
+ },
557
+ {
558
+ "epoch": 0.04,
559
+ "learning_rate": 4.981026784086639e-05,
560
+ "loss": 0.8632,
561
+ "step": 92
562
+ },
563
+ {
564
+ "epoch": 0.04,
565
+ "learning_rate": 4.980608042039862e-05,
566
+ "loss": 0.8798,
567
+ "step": 93
568
+ },
569
+ {
570
+ "epoch": 0.04,
571
+ "learning_rate": 4.980184747426263e-05,
572
+ "loss": 0.9253,
573
+ "step": 94
574
+ },
575
+ {
576
+ "epoch": 0.04,
577
+ "learning_rate": 4.9797569010226995e-05,
578
+ "loss": 0.8305,
579
+ "step": 95
580
+ },
581
+ {
582
+ "epoch": 0.04,
583
+ "learning_rate": 4.979324503614381e-05,
584
+ "loss": 0.9474,
585
+ "step": 96
586
+ },
587
+ {
588
+ "epoch": 0.04,
589
+ "learning_rate": 4.97888755599487e-05,
590
+ "loss": 0.8102,
591
+ "step": 97
592
+ },
593
+ {
594
+ "epoch": 0.04,
595
+ "learning_rate": 4.978446058966081e-05,
596
+ "loss": 0.6445,
597
+ "step": 98
598
+ },
599
+ {
600
+ "epoch": 0.04,
601
+ "learning_rate": 4.978000013338277e-05,
602
+ "loss": 0.8123,
603
+ "step": 99
604
+ },
605
+ {
606
+ "epoch": 0.04,
607
+ "learning_rate": 4.977549419930067e-05,
608
+ "loss": 0.9368,
609
+ "step": 100
610
+ },
611
+ {
612
+ "epoch": 0.04,
613
+ "eval_loss": 0.8984958529472351,
614
+ "eval_runtime": 10.1685,
615
+ "eval_samples_per_second": 3.639,
616
+ "eval_steps_per_second": 0.492,
617
+ "step": 100
618
+ }
619
+ ],
620
+ "logging_steps": 1,
621
+ "max_steps": 2320,
622
+ "num_input_tokens_seen": 0,
623
+ "num_train_epochs": 1,
624
+ "save_steps": 100,
625
+ "total_flos": 1.406258997362688e+17,
626
+ "train_batch_size": 4,
627
+ "trial_name": null,
628
+ "trial_params": null
629
+ }
checkpoint-100/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f72ca16ea9cfad3b34621d2911d6f311c1d481df142920b5b63cd4c1b4222080
3
+ size 4792
checkpoint-1000/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
checkpoint-1000/adapter_config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "up_proj",
23
+ "v_proj",
24
+ "k_proj",
25
+ "o_proj",
26
+ "q_proj",
27
+ "gate_proj",
28
+ "down_proj"
29
+ ],
30
+ "task_type": "CAUSAL_LM",
31
+ "use_rslora": false
32
+ }
checkpoint-1000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e947bdc939167c7ddff6570a7401725a14dcf89ab36517801c768f4ff54aef99
3
+ size 167832240
checkpoint-1000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9889eb20b047e1bcc1e816dffcbe311d5983665abcd16229c33d776586267408
3
+ size 335813306
checkpoint-1000/pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:049c26b844b79121ddd8379f7f69194e63f6fbf6aa007eeac0c66f17eebb8893
3
+ size 888
checkpoint-1000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c31580aa307d1ad63699e364d511103bb6cc34f8732563a737e58ce4e413aa4f
3
+ size 14244
checkpoint-1000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3618c36ad9a167bf62c2bc7886cb955d14dc1043647b009b6aab7e81a49c07a8
3
+ size 1064
checkpoint-1000/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
+ }
checkpoint-1000/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
checkpoint-1000/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": true,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [],
31
+ "bos_token": "<s>",
32
+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
33
+ "clean_up_tokenization_spaces": false,
34
+ "eos_token": "</s>",
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "spaces_between_special_tokens": false,
41
+ "tokenizer_class": "LlamaTokenizer",
42
+ "unk_token": "<unk>",
43
+ "use_default_system_prompt": false
44
+ }
checkpoint-1000/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f72ca16ea9cfad3b34621d2911d6f311c1d481df142920b5b63cd4c1b4222080
3
+ size 4792
checkpoint-1100/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
checkpoint-1100/adapter_config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "up_proj",
23
+ "v_proj",
24
+ "k_proj",
25
+ "o_proj",
26
+ "q_proj",
27
+ "gate_proj",
28
+ "down_proj"
29
+ ],
30
+ "task_type": "CAUSAL_LM",
31
+ "use_rslora": false
32
+ }
checkpoint-1100/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7d3f97bc01a4b66e4054ce6d6dd1988c5e3f47fe0b55a43ae887244d8ae95ff4
3
+ size 167832240
checkpoint-1100/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f91dbc8272b8b92dc2f16edc0ffa88039b2af68920733c451c20333818b7e171
3
+ size 335813306
checkpoint-1100/pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:049c26b844b79121ddd8379f7f69194e63f6fbf6aa007eeac0c66f17eebb8893
3
+ size 888
checkpoint-1100/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:52fbb6b08b2485fbca1fe9155253c7ce53e4c99525df5ddf4a7b0fcdd6575a64
3
+ size 14244
checkpoint-1100/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e342b440dca854de898059198d7050e2840e3b30cb4db23e1128f1ed2045d1ec
3
+ size 1064
checkpoint-1100/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
+ }
checkpoint-1100/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1100/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
checkpoint-1100/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": true,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [],
31
+ "bos_token": "<s>",
32
+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
33
+ "clean_up_tokenization_spaces": false,
34
+ "eos_token": "</s>",
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "padding_side": "right",
39
+ "sp_model_kwargs": {},
40
+ "spaces_between_special_tokens": false,
41
+ "tokenizer_class": "LlamaTokenizer",
42
+ "unk_token": "<unk>",
43
+ "use_default_system_prompt": false
44
+ }
checkpoint-1100/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1100/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f72ca16ea9cfad3b34621d2911d6f311c1d481df142920b5b63cd4c1b4222080
3
+ size 4792
checkpoint-1200/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
checkpoint-1200/adapter_config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Mistral-7B-Instruct-v0.2-dpo-3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "up_proj",
23
+ "v_proj",
24
+ "k_proj",
25
+ "o_proj",
26
+ "q_proj",
27
+ "gate_proj",
28
+ "down_proj"
29
+ ],
30
+ "task_type": "CAUSAL_LM",
31
+ "use_rslora": false
32
+ }
checkpoint-1200/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a7c123196aa716c7ddc726ea8ec2dc970e549f8b606b54eeb71ccfe94481749
3
+ size 167832240
checkpoint-1200/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bccc65a8df88fb2fda9fa9f906b4167a9abc92f89d9d752657f139e274498211
3
+ size 335813306
checkpoint-1200/pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:049c26b844b79121ddd8379f7f69194e63f6fbf6aa007eeac0c66f17eebb8893
3
+ size 888
checkpoint-1200/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:92eb469dfdefffb1ba40adee3829ff30afd8912c3cd7cf139d0d155da2fa5a94
3
+ size 14244
checkpoint-1200/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4ea2ec9fb1515d5822b6558b2f799ac74065753ef73757d4711eeb26440912d8
3
+ size 1064
checkpoint-1200/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
+ }
checkpoint-1200/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1200/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443