felcas93 commited on
Commit
f8ea623
·
verified ·
1 Parent(s): 93e91d8

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. .ipynb_checkpoints/training_summary_rds-checkpoint.json +19 -0
  2. README.md +62 -0
  3. adapter_config.json +43 -0
  4. adapter_model.safetensors +3 -0
  5. checkpoint-1000/README.md +209 -0
  6. checkpoint-1000/adapter_config.json +43 -0
  7. checkpoint-1000/adapter_model.safetensors +3 -0
  8. checkpoint-1000/merges.txt +0 -0
  9. checkpoint-1000/optimizer.pt +3 -0
  10. checkpoint-1000/rng_state.pth +3 -0
  11. checkpoint-1000/scheduler.pt +3 -0
  12. checkpoint-1000/special_tokens_map.json +63 -0
  13. checkpoint-1000/tokenizer.json +0 -0
  14. checkpoint-1000/tokenizer_config.json +357 -0
  15. checkpoint-1000/trainer_state.json +234 -0
  16. checkpoint-1000/training_args.bin +3 -0
  17. checkpoint-1000/vocab.json +0 -0
  18. checkpoint-1500/README.md +209 -0
  19. checkpoint-1500/adapter_config.json +43 -0
  20. checkpoint-1500/adapter_model.safetensors +3 -0
  21. checkpoint-1500/merges.txt +0 -0
  22. checkpoint-1500/optimizer.pt +3 -0
  23. checkpoint-1500/rng_state.pth +3 -0
  24. checkpoint-1500/scheduler.pt +3 -0
  25. checkpoint-1500/special_tokens_map.json +63 -0
  26. checkpoint-1500/tokenizer.json +0 -0
  27. checkpoint-1500/tokenizer_config.json +357 -0
  28. checkpoint-1500/trainer_state.json +334 -0
  29. checkpoint-1500/training_args.bin +3 -0
  30. checkpoint-1500/vocab.json +0 -0
  31. checkpoint-2000/README.md +209 -0
  32. checkpoint-2000/adapter_config.json +43 -0
  33. checkpoint-2000/adapter_model.safetensors +3 -0
  34. checkpoint-2000/merges.txt +0 -0
  35. checkpoint-2000/optimizer.pt +3 -0
  36. checkpoint-2000/rng_state.pth +3 -0
  37. checkpoint-2000/scheduler.pt +3 -0
  38. checkpoint-2000/special_tokens_map.json +63 -0
  39. checkpoint-2000/tokenizer.json +0 -0
  40. checkpoint-2000/tokenizer_config.json +357 -0
  41. checkpoint-2000/trainer_state.json +434 -0
  42. checkpoint-2000/training_args.bin +3 -0
  43. checkpoint-2000/vocab.json +0 -0
  44. checkpoint-2025/README.md +209 -0
  45. checkpoint-2025/adapter_config.json +43 -0
  46. checkpoint-2025/adapter_model.safetensors +3 -0
  47. checkpoint-2025/merges.txt +0 -0
  48. checkpoint-2025/optimizer.pt +3 -0
  49. checkpoint-2025/rng_state.pth +3 -0
  50. checkpoint-2025/scheduler.pt +3 -0
.ipynb_checkpoints/training_summary_rds-checkpoint.json ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "service": "RDS",
3
+ "epochs": 3.0,
4
+ "global_step": 2025,
5
+ "train_runtime_sec": 9535.640872955322,
6
+ "train_samples": 5400,
7
+ "eval_samples": 600,
8
+ "used_bitsandbytes": false,
9
+ "eval_metrics": {
10
+ "eval_loss": 0.1269960105419159,
11
+ "eval_runtime": 112.2786,
12
+ "eval_samples_per_second": 5.344,
13
+ "eval_steps_per_second": 0.668,
14
+ "eval_entropy": 0.12597702960173288,
15
+ "eval_num_tokens": 15377169.0,
16
+ "eval_mean_token_accuracy": 0.9681701477368673,
17
+ "epoch": 3.0
18
+ }
19
+ }
README.md ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: bigcode/starcoder2-7b
3
+ library_name: peft
4
+ model_name: starcoder2_7b_lora_rds
5
+ tags:
6
+ - base_model:adapter:bigcode/starcoder2-7b
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ licence: license
12
+ pipeline_tag: text-generation
13
+ ---
14
+
15
+ # Model Card for starcoder2_7b_lora_rds
16
+
17
+ This model is a fine-tuned version of [bigcode/starcoder2-7b](https://huggingface.co/bigcode/starcoder2-7b).
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
+ This model was trained with SFT.
37
+
38
+ ### Framework versions
39
+
40
+ - PEFT 0.18.0
41
+ - TRL: 0.25.1
42
+ - Transformers: 4.57.3
43
+ - Pytorch: 2.8.0+cu128
44
+ - Datasets: 4.4.1
45
+ - Tokenizers: 0.22.1
46
+
47
+ ## Citations
48
+
49
+
50
+
51
+ Cite TRL as:
52
+
53
+ ```bibtex
54
+ @misc{vonwerra2022trl,
55
+ title = {{TRL: Transformer Reinforcement Learning}},
56
+ author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
57
+ year = 2020,
58
+ journal = {GitHub repository},
59
+ publisher = {GitHub},
60
+ howpublished = {\url{https://github.com/huggingface/trl}}
61
+ }
62
+ ```
adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "bigcode/starcoder2-7b",
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": 32,
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": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "k_proj",
33
+ "v_proj",
34
+ "o_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": null,
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:107a991d7b01bf7d71ef4cde195d1e9daed9f702aae4e7c7a7808aa7fb567d21
3
+ size 58754616
checkpoint-1000/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: bigcode/starcoder2-7b
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:bigcode/starcoder2-7b
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 0.18.0
checkpoint-1000/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "bigcode/starcoder2-7b",
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": 32,
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": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "k_proj",
33
+ "v_proj",
34
+ "o_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": null,
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-1000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f1ad075113d3535619f0f57bfe1c53822fbb0c3155de07da76d036814c3a80a
3
+ size 58754616
checkpoint-1000/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0bc497690d1bbf397adbda307cc63c02dde0187be095789302bb3d551b6e2106
3
+ size 117660107
checkpoint-1000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b525ab0b9b7b12f4275ab7f30e6b241c40b9aa5ffee87b75e3200cdce8895c67
3
+ size 14645
checkpoint-1000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b06201d9403a12d93447a0c39b7483b78fdd17e56d2db9cc8f99c3ba8cf744f1
3
+ size 1465
checkpoint-1000/special_tokens_map.json ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|endoftext|>",
4
+ "<fim_prefix>",
5
+ "<fim_middle>",
6
+ "<fim_suffix>",
7
+ "<fim_pad>",
8
+ "<repo_name>",
9
+ "<file_sep>",
10
+ "<issue_start>",
11
+ "<issue_comment>",
12
+ "<issue_closed>",
13
+ "<jupyter_start>",
14
+ "<jupyter_text>",
15
+ "<jupyter_code>",
16
+ "<jupyter_output>",
17
+ "<jupyter_script>",
18
+ "<empty_output>",
19
+ "<code_to_intermediate>",
20
+ "<intermediate_to_code>",
21
+ "<pr>",
22
+ "<pr_status>",
23
+ "<pr_is_merged>",
24
+ "<pr_base>",
25
+ "<pr_file>",
26
+ "<pr_base_code>",
27
+ "<pr_diff>",
28
+ "<pr_diff_hunk>",
29
+ "<pr_comment>",
30
+ "<pr_event_id>",
31
+ "<pr_review>",
32
+ "<pr_review_state>",
33
+ "<pr_review_comment>",
34
+ "<pr_in_reply_to_review_id>",
35
+ "<pr_in_reply_to_comment_id>",
36
+ "<pr_diff_hunk_comment_line>",
37
+ "<NAME>",
38
+ "<EMAIL>",
39
+ "<KEY>",
40
+ "<PASSWORD>"
41
+ ],
42
+ "bos_token": {
43
+ "content": "<|endoftext|>",
44
+ "lstrip": false,
45
+ "normalized": false,
46
+ "rstrip": false,
47
+ "single_word": false
48
+ },
49
+ "eos_token": {
50
+ "content": "<|endoftext|>",
51
+ "lstrip": false,
52
+ "normalized": false,
53
+ "rstrip": false,
54
+ "single_word": false
55
+ },
56
+ "unk_token": {
57
+ "content": "<|endoftext|>",
58
+ "lstrip": false,
59
+ "normalized": false,
60
+ "rstrip": false,
61
+ "single_word": false
62
+ }
63
+ }
checkpoint-1000/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1000/tokenizer_config.json ADDED
@@ -0,0 +1,357 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "0": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "1": {
13
+ "content": "<fim_prefix>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "2": {
21
+ "content": "<fim_middle>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ },
28
+ "3": {
29
+ "content": "<fim_suffix>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
35
+ },
36
+ "4": {
37
+ "content": "<fim_pad>",
38
+ "lstrip": false,
39
+ "normalized": false,
40
+ "rstrip": false,
41
+ "single_word": false,
42
+ "special": true
43
+ },
44
+ "5": {
45
+ "content": "<repo_name>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
52
+ "6": {
53
+ "content": "<file_sep>",
54
+ "lstrip": false,
55
+ "normalized": false,
56
+ "rstrip": false,
57
+ "single_word": false,
58
+ "special": true
59
+ },
60
+ "7": {
61
+ "content": "<issue_start>",
62
+ "lstrip": false,
63
+ "normalized": false,
64
+ "rstrip": false,
65
+ "single_word": false,
66
+ "special": true
67
+ },
68
+ "8": {
69
+ "content": "<issue_comment>",
70
+ "lstrip": false,
71
+ "normalized": false,
72
+ "rstrip": false,
73
+ "single_word": false,
74
+ "special": true
75
+ },
76
+ "9": {
77
+ "content": "<issue_closed>",
78
+ "lstrip": false,
79
+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
82
+ "special": true
83
+ },
84
+ "10": {
85
+ "content": "<jupyter_start>",
86
+ "lstrip": false,
87
+ "normalized": false,
88
+ "rstrip": false,
89
+ "single_word": false,
90
+ "special": true
91
+ },
92
+ "11": {
93
+ "content": "<jupyter_text>",
94
+ "lstrip": false,
95
+ "normalized": false,
96
+ "rstrip": false,
97
+ "single_word": false,
98
+ "special": true
99
+ },
100
+ "12": {
101
+ "content": "<jupyter_code>",
102
+ "lstrip": false,
103
+ "normalized": false,
104
+ "rstrip": false,
105
+ "single_word": false,
106
+ "special": true
107
+ },
108
+ "13": {
109
+ "content": "<jupyter_output>",
110
+ "lstrip": false,
111
+ "normalized": false,
112
+ "rstrip": false,
113
+ "single_word": false,
114
+ "special": true
115
+ },
116
+ "14": {
117
+ "content": "<jupyter_script>",
118
+ "lstrip": false,
119
+ "normalized": false,
120
+ "rstrip": false,
121
+ "single_word": false,
122
+ "special": true
123
+ },
124
+ "15": {
125
+ "content": "<empty_output>",
126
+ "lstrip": false,
127
+ "normalized": false,
128
+ "rstrip": false,
129
+ "single_word": false,
130
+ "special": true
131
+ },
132
+ "16": {
133
+ "content": "<code_to_intermediate>",
134
+ "lstrip": false,
135
+ "normalized": false,
136
+ "rstrip": false,
137
+ "single_word": false,
138
+ "special": true
139
+ },
140
+ "17": {
141
+ "content": "<intermediate_to_code>",
142
+ "lstrip": false,
143
+ "normalized": false,
144
+ "rstrip": false,
145
+ "single_word": false,
146
+ "special": true
147
+ },
148
+ "18": {
149
+ "content": "<pr>",
150
+ "lstrip": false,
151
+ "normalized": false,
152
+ "rstrip": false,
153
+ "single_word": false,
154
+ "special": true
155
+ },
156
+ "19": {
157
+ "content": "<pr_status>",
158
+ "lstrip": false,
159
+ "normalized": false,
160
+ "rstrip": false,
161
+ "single_word": false,
162
+ "special": true
163
+ },
164
+ "20": {
165
+ "content": "<pr_is_merged>",
166
+ "lstrip": false,
167
+ "normalized": false,
168
+ "rstrip": false,
169
+ "single_word": false,
170
+ "special": true
171
+ },
172
+ "21": {
173
+ "content": "<pr_base>",
174
+ "lstrip": false,
175
+ "normalized": false,
176
+ "rstrip": false,
177
+ "single_word": false,
178
+ "special": true
179
+ },
180
+ "22": {
181
+ "content": "<pr_file>",
182
+ "lstrip": false,
183
+ "normalized": false,
184
+ "rstrip": false,
185
+ "single_word": false,
186
+ "special": true
187
+ },
188
+ "23": {
189
+ "content": "<pr_base_code>",
190
+ "lstrip": false,
191
+ "normalized": false,
192
+ "rstrip": false,
193
+ "single_word": false,
194
+ "special": true
195
+ },
196
+ "24": {
197
+ "content": "<pr_diff>",
198
+ "lstrip": false,
199
+ "normalized": false,
200
+ "rstrip": false,
201
+ "single_word": false,
202
+ "special": true
203
+ },
204
+ "25": {
205
+ "content": "<pr_diff_hunk>",
206
+ "lstrip": false,
207
+ "normalized": false,
208
+ "rstrip": false,
209
+ "single_word": false,
210
+ "special": true
211
+ },
212
+ "26": {
213
+ "content": "<pr_comment>",
214
+ "lstrip": false,
215
+ "normalized": false,
216
+ "rstrip": false,
217
+ "single_word": false,
218
+ "special": true
219
+ },
220
+ "27": {
221
+ "content": "<pr_event_id>",
222
+ "lstrip": false,
223
+ "normalized": false,
224
+ "rstrip": false,
225
+ "single_word": false,
226
+ "special": true
227
+ },
228
+ "28": {
229
+ "content": "<pr_review>",
230
+ "lstrip": false,
231
+ "normalized": false,
232
+ "rstrip": false,
233
+ "single_word": false,
234
+ "special": true
235
+ },
236
+ "29": {
237
+ "content": "<pr_review_state>",
238
+ "lstrip": false,
239
+ "normalized": false,
240
+ "rstrip": false,
241
+ "single_word": false,
242
+ "special": true
243
+ },
244
+ "30": {
245
+ "content": "<pr_review_comment>",
246
+ "lstrip": false,
247
+ "normalized": false,
248
+ "rstrip": false,
249
+ "single_word": false,
250
+ "special": true
251
+ },
252
+ "31": {
253
+ "content": "<pr_in_reply_to_review_id>",
254
+ "lstrip": false,
255
+ "normalized": false,
256
+ "rstrip": false,
257
+ "single_word": false,
258
+ "special": true
259
+ },
260
+ "32": {
261
+ "content": "<pr_in_reply_to_comment_id>",
262
+ "lstrip": false,
263
+ "normalized": false,
264
+ "rstrip": false,
265
+ "single_word": false,
266
+ "special": true
267
+ },
268
+ "33": {
269
+ "content": "<pr_diff_hunk_comment_line>",
270
+ "lstrip": false,
271
+ "normalized": false,
272
+ "rstrip": false,
273
+ "single_word": false,
274
+ "special": true
275
+ },
276
+ "34": {
277
+ "content": "<NAME>",
278
+ "lstrip": false,
279
+ "normalized": false,
280
+ "rstrip": false,
281
+ "single_word": false,
282
+ "special": true
283
+ },
284
+ "35": {
285
+ "content": "<EMAIL>",
286
+ "lstrip": false,
287
+ "normalized": false,
288
+ "rstrip": false,
289
+ "single_word": false,
290
+ "special": true
291
+ },
292
+ "36": {
293
+ "content": "<KEY>",
294
+ "lstrip": false,
295
+ "normalized": false,
296
+ "rstrip": false,
297
+ "single_word": false,
298
+ "special": true
299
+ },
300
+ "37": {
301
+ "content": "<PASSWORD>",
302
+ "lstrip": false,
303
+ "normalized": false,
304
+ "rstrip": false,
305
+ "single_word": false,
306
+ "special": true
307
+ }
308
+ },
309
+ "additional_special_tokens": [
310
+ "<|endoftext|>",
311
+ "<fim_prefix>",
312
+ "<fim_middle>",
313
+ "<fim_suffix>",
314
+ "<fim_pad>",
315
+ "<repo_name>",
316
+ "<file_sep>",
317
+ "<issue_start>",
318
+ "<issue_comment>",
319
+ "<issue_closed>",
320
+ "<jupyter_start>",
321
+ "<jupyter_text>",
322
+ "<jupyter_code>",
323
+ "<jupyter_output>",
324
+ "<jupyter_script>",
325
+ "<empty_output>",
326
+ "<code_to_intermediate>",
327
+ "<intermediate_to_code>",
328
+ "<pr>",
329
+ "<pr_status>",
330
+ "<pr_is_merged>",
331
+ "<pr_base>",
332
+ "<pr_file>",
333
+ "<pr_base_code>",
334
+ "<pr_diff>",
335
+ "<pr_diff_hunk>",
336
+ "<pr_comment>",
337
+ "<pr_event_id>",
338
+ "<pr_review>",
339
+ "<pr_review_state>",
340
+ "<pr_review_comment>",
341
+ "<pr_in_reply_to_review_id>",
342
+ "<pr_in_reply_to_comment_id>",
343
+ "<pr_diff_hunk_comment_line>",
344
+ "<NAME>",
345
+ "<EMAIL>",
346
+ "<KEY>",
347
+ "<PASSWORD>"
348
+ ],
349
+ "bos_token": "<|endoftext|>",
350
+ "clean_up_tokenization_spaces": true,
351
+ "eos_token": "<|endoftext|>",
352
+ "extra_special_tokens": {},
353
+ "model_max_length": 1000000000000000019884624838656,
354
+ "tokenizer_class": "GPT2Tokenizer",
355
+ "unk_token": "<|endoftext|>",
356
+ "vocab_size": 49152
357
+ }
checkpoint-1000/trainer_state.json ADDED
@@ -0,0 +1,234 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.4814814814814814,
6
+ "eval_steps": 500,
7
+ "global_step": 1000,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.9540774886310102,
14
+ "epoch": 0.07407407407407407,
15
+ "grad_norm": 0.8241696953773499,
16
+ "learning_rate": 8.032786885245902e-05,
17
+ "loss": 1.7451,
18
+ "mean_token_accuracy": 0.6189013833552599,
19
+ "num_tokens": 379953.0,
20
+ "step": 50
21
+ },
22
+ {
23
+ "entropy": 0.5046265083923935,
24
+ "epoch": 0.14814814814814814,
25
+ "grad_norm": 4.424446105957031,
26
+ "learning_rate": 9.990765991730485e-05,
27
+ "loss": 0.4302,
28
+ "mean_token_accuracy": 0.8861582314968109,
29
+ "num_tokens": 757047.0,
30
+ "step": 100
31
+ },
32
+ {
33
+ "entropy": 0.24775007627904416,
34
+ "epoch": 0.2222222222222222,
35
+ "grad_norm": 0.30575165152549744,
36
+ "learning_rate": 9.950545603782162e-05,
37
+ "loss": 0.2323,
38
+ "mean_token_accuracy": 0.940535937026143,
39
+ "num_tokens": 1134378.0,
40
+ "step": 150
41
+ },
42
+ {
43
+ "entropy": 0.1925063591822982,
44
+ "epoch": 0.2962962962962963,
45
+ "grad_norm": 0.24072137475013733,
46
+ "learning_rate": 9.878674879048427e-05,
47
+ "loss": 0.1856,
48
+ "mean_token_accuracy": 0.9529062640666962,
49
+ "num_tokens": 1516152.0,
50
+ "step": 200
51
+ },
52
+ {
53
+ "entropy": 0.18322961997240783,
54
+ "epoch": 0.37037037037037035,
55
+ "grad_norm": 0.18854060769081116,
56
+ "learning_rate": 9.775613308830824e-05,
57
+ "loss": 0.1775,
58
+ "mean_token_accuracy": 0.9546041788160801,
59
+ "num_tokens": 1896494.0,
60
+ "step": 250
61
+ },
62
+ {
63
+ "entropy": 0.17187482433393597,
64
+ "epoch": 0.4444444444444444,
65
+ "grad_norm": 0.18019668757915497,
66
+ "learning_rate": 9.642019796948866e-05,
67
+ "loss": 0.164,
68
+ "mean_token_accuracy": 0.9579361644387245,
69
+ "num_tokens": 2277194.0,
70
+ "step": 300
71
+ },
72
+ {
73
+ "entropy": 0.16193925650790333,
74
+ "epoch": 0.5185185185185185,
75
+ "grad_norm": 0.23759332299232483,
76
+ "learning_rate": 9.478748447168449e-05,
77
+ "loss": 0.1539,
78
+ "mean_token_accuracy": 0.9614081564545631,
79
+ "num_tokens": 2658243.0,
80
+ "step": 350
81
+ },
82
+ {
83
+ "entropy": 0.15039873549714686,
84
+ "epoch": 0.5925925925925926,
85
+ "grad_norm": 0.2590758204460144,
86
+ "learning_rate": 9.28684310265789e-05,
87
+ "loss": 0.1443,
88
+ "mean_token_accuracy": 0.9650989197194576,
89
+ "num_tokens": 3041430.0,
90
+ "step": 400
91
+ },
92
+ {
93
+ "entropy": 0.14228019634261727,
94
+ "epoch": 0.6666666666666666,
95
+ "grad_norm": 0.18062612414360046,
96
+ "learning_rate": 9.067530672382544e-05,
97
+ "loss": 0.1366,
98
+ "mean_token_accuracy": 0.9667340110242367,
99
+ "num_tokens": 3422368.0,
100
+ "step": 450
101
+ },
102
+ {
103
+ "entropy": 0.1391275341436267,
104
+ "epoch": 0.7407407407407407,
105
+ "grad_norm": 0.1984509527683258,
106
+ "learning_rate": 8.822213287104348e-05,
107
+ "loss": 0.1352,
108
+ "mean_token_accuracy": 0.9674024738371372,
109
+ "num_tokens": 3801968.0,
110
+ "step": 500
111
+ },
112
+ {
113
+ "entropy": 0.13673329239711166,
114
+ "epoch": 0.8148148148148148,
115
+ "grad_norm": 0.13088534772396088,
116
+ "learning_rate": 8.552459335135381e-05,
117
+ "loss": 0.1354,
118
+ "mean_token_accuracy": 0.9673544447124004,
119
+ "num_tokens": 4182102.0,
120
+ "step": 550
121
+ },
122
+ {
123
+ "entropy": 0.13533455861732363,
124
+ "epoch": 0.8888888888888888,
125
+ "grad_norm": 0.33587542176246643,
126
+ "learning_rate": 8.259993435156559e-05,
127
+ "loss": 0.1325,
128
+ "mean_token_accuracy": 0.9676820485293866,
129
+ "num_tokens": 4561998.0,
130
+ "step": 600
131
+ },
132
+ {
133
+ "entropy": 0.13281562993302942,
134
+ "epoch": 0.9629629629629629,
135
+ "grad_norm": 0.11626797914505005,
136
+ "learning_rate": 7.946685410208296e-05,
137
+ "loss": 0.1313,
138
+ "mean_token_accuracy": 0.9678142921626568,
139
+ "num_tokens": 4936347.0,
140
+ "step": 650
141
+ },
142
+ {
143
+ "entropy": 0.1338025047816336,
144
+ "epoch": 1.037037037037037,
145
+ "grad_norm": 0.10883153975009918,
146
+ "learning_rate": 7.614538333345735e-05,
147
+ "loss": 0.1328,
148
+ "mean_token_accuracy": 0.9673172944784164,
149
+ "num_tokens": 5313396.0,
150
+ "step": 700
151
+ },
152
+ {
153
+ "entropy": 0.1330988533422351,
154
+ "epoch": 1.1111111111111112,
155
+ "grad_norm": 0.14333182573318481,
156
+ "learning_rate": 7.265675721386285e-05,
157
+ "loss": 0.1317,
158
+ "mean_token_accuracy": 0.9678454534709453,
159
+ "num_tokens": 5694821.0,
160
+ "step": 750
161
+ },
162
+ {
163
+ "entropy": 0.1315150342695415,
164
+ "epoch": 1.1851851851851851,
165
+ "grad_norm": 0.07893866300582886,
166
+ "learning_rate": 6.902327958623736e-05,
167
+ "loss": 0.131,
168
+ "mean_token_accuracy": 0.9678919970989227,
169
+ "num_tokens": 6071147.0,
170
+ "step": 800
171
+ },
172
+ {
173
+ "entropy": 0.1348141137883067,
174
+ "epoch": 1.2592592592592593,
175
+ "grad_norm": 0.10548827797174454,
176
+ "learning_rate": 6.526818037306228e-05,
177
+ "loss": 0.1337,
178
+ "mean_token_accuracy": 0.9671075843274594,
179
+ "num_tokens": 6454454.0,
180
+ "step": 850
181
+ },
182
+ {
183
+ "entropy": 0.12924523117020725,
184
+ "epoch": 1.3333333333333333,
185
+ "grad_norm": 0.13734276592731476,
186
+ "learning_rate": 6.14154670604355e-05,
187
+ "loss": 0.1294,
188
+ "mean_token_accuracy": 0.9686036820709706,
189
+ "num_tokens": 6831407.0,
190
+ "step": 900
191
+ },
192
+ {
193
+ "entropy": 0.13089272173121572,
194
+ "epoch": 1.4074074074074074,
195
+ "grad_norm": 0.062484513968229294,
196
+ "learning_rate": 5.7489771210944564e-05,
197
+ "loss": 0.1304,
198
+ "mean_token_accuracy": 0.9679886139929295,
199
+ "num_tokens": 7211253.0,
200
+ "step": 950
201
+ },
202
+ {
203
+ "entropy": 0.1295284123532474,
204
+ "epoch": 1.4814814814814814,
205
+ "grad_norm": 0.07434429228305817,
206
+ "learning_rate": 5.351619098663021e-05,
207
+ "loss": 0.1289,
208
+ "mean_token_accuracy": 0.9682336232066154,
209
+ "num_tokens": 7591172.0,
210
+ "step": 1000
211
+ }
212
+ ],
213
+ "logging_steps": 50,
214
+ "max_steps": 2025,
215
+ "num_input_tokens_seen": 0,
216
+ "num_train_epochs": 3,
217
+ "save_steps": 500,
218
+ "stateful_callbacks": {
219
+ "TrainerControl": {
220
+ "args": {
221
+ "should_epoch_stop": false,
222
+ "should_evaluate": false,
223
+ "should_log": false,
224
+ "should_save": true,
225
+ "should_training_stop": false
226
+ },
227
+ "attributes": {}
228
+ }
229
+ },
230
+ "total_flos": 3.171035147315036e+17,
231
+ "train_batch_size": 1,
232
+ "trial_name": null,
233
+ "trial_params": null
234
+ }
checkpoint-1000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:972906ac2311d1411092b921ffee2b39397b24618f8f2b157e1215061dd47de3
3
+ size 6225
checkpoint-1000/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1500/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: bigcode/starcoder2-7b
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:bigcode/starcoder2-7b
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 0.18.0
checkpoint-1500/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "bigcode/starcoder2-7b",
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": 32,
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": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "k_proj",
33
+ "v_proj",
34
+ "o_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": null,
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-1500/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:32d076d94593c22c64f81f09cfbf6739821bb98fe792f71d5e403ece0433e168
3
+ size 58754616
checkpoint-1500/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1500/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5d16a138a36c8b643b0c457df330d670e1b6bdfd6ec4d7575fef2d7e8f72c6e6
3
+ size 117660107
checkpoint-1500/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:33105afe91c973cbc936a57ab8d9a1b0ac4b524c3e4f241f9bbbc0338dd05cc1
3
+ size 14645
checkpoint-1500/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6b10d09adf0489af5dc688ca572941043ef06e06d7551388176d2e6574474a5a
3
+ size 1465
checkpoint-1500/special_tokens_map.json ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|endoftext|>",
4
+ "<fim_prefix>",
5
+ "<fim_middle>",
6
+ "<fim_suffix>",
7
+ "<fim_pad>",
8
+ "<repo_name>",
9
+ "<file_sep>",
10
+ "<issue_start>",
11
+ "<issue_comment>",
12
+ "<issue_closed>",
13
+ "<jupyter_start>",
14
+ "<jupyter_text>",
15
+ "<jupyter_code>",
16
+ "<jupyter_output>",
17
+ "<jupyter_script>",
18
+ "<empty_output>",
19
+ "<code_to_intermediate>",
20
+ "<intermediate_to_code>",
21
+ "<pr>",
22
+ "<pr_status>",
23
+ "<pr_is_merged>",
24
+ "<pr_base>",
25
+ "<pr_file>",
26
+ "<pr_base_code>",
27
+ "<pr_diff>",
28
+ "<pr_diff_hunk>",
29
+ "<pr_comment>",
30
+ "<pr_event_id>",
31
+ "<pr_review>",
32
+ "<pr_review_state>",
33
+ "<pr_review_comment>",
34
+ "<pr_in_reply_to_review_id>",
35
+ "<pr_in_reply_to_comment_id>",
36
+ "<pr_diff_hunk_comment_line>",
37
+ "<NAME>",
38
+ "<EMAIL>",
39
+ "<KEY>",
40
+ "<PASSWORD>"
41
+ ],
42
+ "bos_token": {
43
+ "content": "<|endoftext|>",
44
+ "lstrip": false,
45
+ "normalized": false,
46
+ "rstrip": false,
47
+ "single_word": false
48
+ },
49
+ "eos_token": {
50
+ "content": "<|endoftext|>",
51
+ "lstrip": false,
52
+ "normalized": false,
53
+ "rstrip": false,
54
+ "single_word": false
55
+ },
56
+ "unk_token": {
57
+ "content": "<|endoftext|>",
58
+ "lstrip": false,
59
+ "normalized": false,
60
+ "rstrip": false,
61
+ "single_word": false
62
+ }
63
+ }
checkpoint-1500/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1500/tokenizer_config.json ADDED
@@ -0,0 +1,357 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "0": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "1": {
13
+ "content": "<fim_prefix>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "2": {
21
+ "content": "<fim_middle>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ },
28
+ "3": {
29
+ "content": "<fim_suffix>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
35
+ },
36
+ "4": {
37
+ "content": "<fim_pad>",
38
+ "lstrip": false,
39
+ "normalized": false,
40
+ "rstrip": false,
41
+ "single_word": false,
42
+ "special": true
43
+ },
44
+ "5": {
45
+ "content": "<repo_name>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
52
+ "6": {
53
+ "content": "<file_sep>",
54
+ "lstrip": false,
55
+ "normalized": false,
56
+ "rstrip": false,
57
+ "single_word": false,
58
+ "special": true
59
+ },
60
+ "7": {
61
+ "content": "<issue_start>",
62
+ "lstrip": false,
63
+ "normalized": false,
64
+ "rstrip": false,
65
+ "single_word": false,
66
+ "special": true
67
+ },
68
+ "8": {
69
+ "content": "<issue_comment>",
70
+ "lstrip": false,
71
+ "normalized": false,
72
+ "rstrip": false,
73
+ "single_word": false,
74
+ "special": true
75
+ },
76
+ "9": {
77
+ "content": "<issue_closed>",
78
+ "lstrip": false,
79
+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
82
+ "special": true
83
+ },
84
+ "10": {
85
+ "content": "<jupyter_start>",
86
+ "lstrip": false,
87
+ "normalized": false,
88
+ "rstrip": false,
89
+ "single_word": false,
90
+ "special": true
91
+ },
92
+ "11": {
93
+ "content": "<jupyter_text>",
94
+ "lstrip": false,
95
+ "normalized": false,
96
+ "rstrip": false,
97
+ "single_word": false,
98
+ "special": true
99
+ },
100
+ "12": {
101
+ "content": "<jupyter_code>",
102
+ "lstrip": false,
103
+ "normalized": false,
104
+ "rstrip": false,
105
+ "single_word": false,
106
+ "special": true
107
+ },
108
+ "13": {
109
+ "content": "<jupyter_output>",
110
+ "lstrip": false,
111
+ "normalized": false,
112
+ "rstrip": false,
113
+ "single_word": false,
114
+ "special": true
115
+ },
116
+ "14": {
117
+ "content": "<jupyter_script>",
118
+ "lstrip": false,
119
+ "normalized": false,
120
+ "rstrip": false,
121
+ "single_word": false,
122
+ "special": true
123
+ },
124
+ "15": {
125
+ "content": "<empty_output>",
126
+ "lstrip": false,
127
+ "normalized": false,
128
+ "rstrip": false,
129
+ "single_word": false,
130
+ "special": true
131
+ },
132
+ "16": {
133
+ "content": "<code_to_intermediate>",
134
+ "lstrip": false,
135
+ "normalized": false,
136
+ "rstrip": false,
137
+ "single_word": false,
138
+ "special": true
139
+ },
140
+ "17": {
141
+ "content": "<intermediate_to_code>",
142
+ "lstrip": false,
143
+ "normalized": false,
144
+ "rstrip": false,
145
+ "single_word": false,
146
+ "special": true
147
+ },
148
+ "18": {
149
+ "content": "<pr>",
150
+ "lstrip": false,
151
+ "normalized": false,
152
+ "rstrip": false,
153
+ "single_word": false,
154
+ "special": true
155
+ },
156
+ "19": {
157
+ "content": "<pr_status>",
158
+ "lstrip": false,
159
+ "normalized": false,
160
+ "rstrip": false,
161
+ "single_word": false,
162
+ "special": true
163
+ },
164
+ "20": {
165
+ "content": "<pr_is_merged>",
166
+ "lstrip": false,
167
+ "normalized": false,
168
+ "rstrip": false,
169
+ "single_word": false,
170
+ "special": true
171
+ },
172
+ "21": {
173
+ "content": "<pr_base>",
174
+ "lstrip": false,
175
+ "normalized": false,
176
+ "rstrip": false,
177
+ "single_word": false,
178
+ "special": true
179
+ },
180
+ "22": {
181
+ "content": "<pr_file>",
182
+ "lstrip": false,
183
+ "normalized": false,
184
+ "rstrip": false,
185
+ "single_word": false,
186
+ "special": true
187
+ },
188
+ "23": {
189
+ "content": "<pr_base_code>",
190
+ "lstrip": false,
191
+ "normalized": false,
192
+ "rstrip": false,
193
+ "single_word": false,
194
+ "special": true
195
+ },
196
+ "24": {
197
+ "content": "<pr_diff>",
198
+ "lstrip": false,
199
+ "normalized": false,
200
+ "rstrip": false,
201
+ "single_word": false,
202
+ "special": true
203
+ },
204
+ "25": {
205
+ "content": "<pr_diff_hunk>",
206
+ "lstrip": false,
207
+ "normalized": false,
208
+ "rstrip": false,
209
+ "single_word": false,
210
+ "special": true
211
+ },
212
+ "26": {
213
+ "content": "<pr_comment>",
214
+ "lstrip": false,
215
+ "normalized": false,
216
+ "rstrip": false,
217
+ "single_word": false,
218
+ "special": true
219
+ },
220
+ "27": {
221
+ "content": "<pr_event_id>",
222
+ "lstrip": false,
223
+ "normalized": false,
224
+ "rstrip": false,
225
+ "single_word": false,
226
+ "special": true
227
+ },
228
+ "28": {
229
+ "content": "<pr_review>",
230
+ "lstrip": false,
231
+ "normalized": false,
232
+ "rstrip": false,
233
+ "single_word": false,
234
+ "special": true
235
+ },
236
+ "29": {
237
+ "content": "<pr_review_state>",
238
+ "lstrip": false,
239
+ "normalized": false,
240
+ "rstrip": false,
241
+ "single_word": false,
242
+ "special": true
243
+ },
244
+ "30": {
245
+ "content": "<pr_review_comment>",
246
+ "lstrip": false,
247
+ "normalized": false,
248
+ "rstrip": false,
249
+ "single_word": false,
250
+ "special": true
251
+ },
252
+ "31": {
253
+ "content": "<pr_in_reply_to_review_id>",
254
+ "lstrip": false,
255
+ "normalized": false,
256
+ "rstrip": false,
257
+ "single_word": false,
258
+ "special": true
259
+ },
260
+ "32": {
261
+ "content": "<pr_in_reply_to_comment_id>",
262
+ "lstrip": false,
263
+ "normalized": false,
264
+ "rstrip": false,
265
+ "single_word": false,
266
+ "special": true
267
+ },
268
+ "33": {
269
+ "content": "<pr_diff_hunk_comment_line>",
270
+ "lstrip": false,
271
+ "normalized": false,
272
+ "rstrip": false,
273
+ "single_word": false,
274
+ "special": true
275
+ },
276
+ "34": {
277
+ "content": "<NAME>",
278
+ "lstrip": false,
279
+ "normalized": false,
280
+ "rstrip": false,
281
+ "single_word": false,
282
+ "special": true
283
+ },
284
+ "35": {
285
+ "content": "<EMAIL>",
286
+ "lstrip": false,
287
+ "normalized": false,
288
+ "rstrip": false,
289
+ "single_word": false,
290
+ "special": true
291
+ },
292
+ "36": {
293
+ "content": "<KEY>",
294
+ "lstrip": false,
295
+ "normalized": false,
296
+ "rstrip": false,
297
+ "single_word": false,
298
+ "special": true
299
+ },
300
+ "37": {
301
+ "content": "<PASSWORD>",
302
+ "lstrip": false,
303
+ "normalized": false,
304
+ "rstrip": false,
305
+ "single_word": false,
306
+ "special": true
307
+ }
308
+ },
309
+ "additional_special_tokens": [
310
+ "<|endoftext|>",
311
+ "<fim_prefix>",
312
+ "<fim_middle>",
313
+ "<fim_suffix>",
314
+ "<fim_pad>",
315
+ "<repo_name>",
316
+ "<file_sep>",
317
+ "<issue_start>",
318
+ "<issue_comment>",
319
+ "<issue_closed>",
320
+ "<jupyter_start>",
321
+ "<jupyter_text>",
322
+ "<jupyter_code>",
323
+ "<jupyter_output>",
324
+ "<jupyter_script>",
325
+ "<empty_output>",
326
+ "<code_to_intermediate>",
327
+ "<intermediate_to_code>",
328
+ "<pr>",
329
+ "<pr_status>",
330
+ "<pr_is_merged>",
331
+ "<pr_base>",
332
+ "<pr_file>",
333
+ "<pr_base_code>",
334
+ "<pr_diff>",
335
+ "<pr_diff_hunk>",
336
+ "<pr_comment>",
337
+ "<pr_event_id>",
338
+ "<pr_review>",
339
+ "<pr_review_state>",
340
+ "<pr_review_comment>",
341
+ "<pr_in_reply_to_review_id>",
342
+ "<pr_in_reply_to_comment_id>",
343
+ "<pr_diff_hunk_comment_line>",
344
+ "<NAME>",
345
+ "<EMAIL>",
346
+ "<KEY>",
347
+ "<PASSWORD>"
348
+ ],
349
+ "bos_token": "<|endoftext|>",
350
+ "clean_up_tokenization_spaces": true,
351
+ "eos_token": "<|endoftext|>",
352
+ "extra_special_tokens": {},
353
+ "model_max_length": 1000000000000000019884624838656,
354
+ "tokenizer_class": "GPT2Tokenizer",
355
+ "unk_token": "<|endoftext|>",
356
+ "vocab_size": 49152
357
+ }
checkpoint-1500/trainer_state.json ADDED
@@ -0,0 +1,334 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.2222222222222223,
6
+ "eval_steps": 500,
7
+ "global_step": 1500,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.9540774886310102,
14
+ "epoch": 0.07407407407407407,
15
+ "grad_norm": 0.8241696953773499,
16
+ "learning_rate": 8.032786885245902e-05,
17
+ "loss": 1.7451,
18
+ "mean_token_accuracy": 0.6189013833552599,
19
+ "num_tokens": 379953.0,
20
+ "step": 50
21
+ },
22
+ {
23
+ "entropy": 0.5046265083923935,
24
+ "epoch": 0.14814814814814814,
25
+ "grad_norm": 4.424446105957031,
26
+ "learning_rate": 9.990765991730485e-05,
27
+ "loss": 0.4302,
28
+ "mean_token_accuracy": 0.8861582314968109,
29
+ "num_tokens": 757047.0,
30
+ "step": 100
31
+ },
32
+ {
33
+ "entropy": 0.24775007627904416,
34
+ "epoch": 0.2222222222222222,
35
+ "grad_norm": 0.30575165152549744,
36
+ "learning_rate": 9.950545603782162e-05,
37
+ "loss": 0.2323,
38
+ "mean_token_accuracy": 0.940535937026143,
39
+ "num_tokens": 1134378.0,
40
+ "step": 150
41
+ },
42
+ {
43
+ "entropy": 0.1925063591822982,
44
+ "epoch": 0.2962962962962963,
45
+ "grad_norm": 0.24072137475013733,
46
+ "learning_rate": 9.878674879048427e-05,
47
+ "loss": 0.1856,
48
+ "mean_token_accuracy": 0.9529062640666962,
49
+ "num_tokens": 1516152.0,
50
+ "step": 200
51
+ },
52
+ {
53
+ "entropy": 0.18322961997240783,
54
+ "epoch": 0.37037037037037035,
55
+ "grad_norm": 0.18854060769081116,
56
+ "learning_rate": 9.775613308830824e-05,
57
+ "loss": 0.1775,
58
+ "mean_token_accuracy": 0.9546041788160801,
59
+ "num_tokens": 1896494.0,
60
+ "step": 250
61
+ },
62
+ {
63
+ "entropy": 0.17187482433393597,
64
+ "epoch": 0.4444444444444444,
65
+ "grad_norm": 0.18019668757915497,
66
+ "learning_rate": 9.642019796948866e-05,
67
+ "loss": 0.164,
68
+ "mean_token_accuracy": 0.9579361644387245,
69
+ "num_tokens": 2277194.0,
70
+ "step": 300
71
+ },
72
+ {
73
+ "entropy": 0.16193925650790333,
74
+ "epoch": 0.5185185185185185,
75
+ "grad_norm": 0.23759332299232483,
76
+ "learning_rate": 9.478748447168449e-05,
77
+ "loss": 0.1539,
78
+ "mean_token_accuracy": 0.9614081564545631,
79
+ "num_tokens": 2658243.0,
80
+ "step": 350
81
+ },
82
+ {
83
+ "entropy": 0.15039873549714686,
84
+ "epoch": 0.5925925925925926,
85
+ "grad_norm": 0.2590758204460144,
86
+ "learning_rate": 9.28684310265789e-05,
87
+ "loss": 0.1443,
88
+ "mean_token_accuracy": 0.9650989197194576,
89
+ "num_tokens": 3041430.0,
90
+ "step": 400
91
+ },
92
+ {
93
+ "entropy": 0.14228019634261727,
94
+ "epoch": 0.6666666666666666,
95
+ "grad_norm": 0.18062612414360046,
96
+ "learning_rate": 9.067530672382544e-05,
97
+ "loss": 0.1366,
98
+ "mean_token_accuracy": 0.9667340110242367,
99
+ "num_tokens": 3422368.0,
100
+ "step": 450
101
+ },
102
+ {
103
+ "entropy": 0.1391275341436267,
104
+ "epoch": 0.7407407407407407,
105
+ "grad_norm": 0.1984509527683258,
106
+ "learning_rate": 8.822213287104348e-05,
107
+ "loss": 0.1352,
108
+ "mean_token_accuracy": 0.9674024738371372,
109
+ "num_tokens": 3801968.0,
110
+ "step": 500
111
+ },
112
+ {
113
+ "entropy": 0.13673329239711166,
114
+ "epoch": 0.8148148148148148,
115
+ "grad_norm": 0.13088534772396088,
116
+ "learning_rate": 8.552459335135381e-05,
117
+ "loss": 0.1354,
118
+ "mean_token_accuracy": 0.9673544447124004,
119
+ "num_tokens": 4182102.0,
120
+ "step": 550
121
+ },
122
+ {
123
+ "entropy": 0.13533455861732363,
124
+ "epoch": 0.8888888888888888,
125
+ "grad_norm": 0.33587542176246643,
126
+ "learning_rate": 8.259993435156559e-05,
127
+ "loss": 0.1325,
128
+ "mean_token_accuracy": 0.9676820485293866,
129
+ "num_tokens": 4561998.0,
130
+ "step": 600
131
+ },
132
+ {
133
+ "entropy": 0.13281562993302942,
134
+ "epoch": 0.9629629629629629,
135
+ "grad_norm": 0.11626797914505005,
136
+ "learning_rate": 7.946685410208296e-05,
137
+ "loss": 0.1313,
138
+ "mean_token_accuracy": 0.9678142921626568,
139
+ "num_tokens": 4936347.0,
140
+ "step": 650
141
+ },
142
+ {
143
+ "entropy": 0.1338025047816336,
144
+ "epoch": 1.037037037037037,
145
+ "grad_norm": 0.10883153975009918,
146
+ "learning_rate": 7.614538333345735e-05,
147
+ "loss": 0.1328,
148
+ "mean_token_accuracy": 0.9673172944784164,
149
+ "num_tokens": 5313396.0,
150
+ "step": 700
151
+ },
152
+ {
153
+ "entropy": 0.1330988533422351,
154
+ "epoch": 1.1111111111111112,
155
+ "grad_norm": 0.14333182573318481,
156
+ "learning_rate": 7.265675721386285e-05,
157
+ "loss": 0.1317,
158
+ "mean_token_accuracy": 0.9678454534709453,
159
+ "num_tokens": 5694821.0,
160
+ "step": 750
161
+ },
162
+ {
163
+ "entropy": 0.1315150342695415,
164
+ "epoch": 1.1851851851851851,
165
+ "grad_norm": 0.07893866300582886,
166
+ "learning_rate": 6.902327958623736e-05,
167
+ "loss": 0.131,
168
+ "mean_token_accuracy": 0.9678919970989227,
169
+ "num_tokens": 6071147.0,
170
+ "step": 800
171
+ },
172
+ {
173
+ "entropy": 0.1348141137883067,
174
+ "epoch": 1.2592592592592593,
175
+ "grad_norm": 0.10548827797174454,
176
+ "learning_rate": 6.526818037306228e-05,
177
+ "loss": 0.1337,
178
+ "mean_token_accuracy": 0.9671075843274594,
179
+ "num_tokens": 6454454.0,
180
+ "step": 850
181
+ },
182
+ {
183
+ "entropy": 0.12924523117020725,
184
+ "epoch": 1.3333333333333333,
185
+ "grad_norm": 0.13734276592731476,
186
+ "learning_rate": 6.14154670604355e-05,
187
+ "loss": 0.1294,
188
+ "mean_token_accuracy": 0.9686036820709706,
189
+ "num_tokens": 6831407.0,
190
+ "step": 900
191
+ },
192
+ {
193
+ "entropy": 0.13089272173121572,
194
+ "epoch": 1.4074074074074074,
195
+ "grad_norm": 0.062484513968229294,
196
+ "learning_rate": 5.7489771210944564e-05,
197
+ "loss": 0.1304,
198
+ "mean_token_accuracy": 0.9679886139929295,
199
+ "num_tokens": 7211253.0,
200
+ "step": 950
201
+ },
202
+ {
203
+ "entropy": 0.1295284123532474,
204
+ "epoch": 1.4814814814814814,
205
+ "grad_norm": 0.07434429228305817,
206
+ "learning_rate": 5.351619098663021e-05,
207
+ "loss": 0.1289,
208
+ "mean_token_accuracy": 0.9682336232066154,
209
+ "num_tokens": 7591172.0,
210
+ "step": 1000
211
+ },
212
+ {
213
+ "entropy": 0.13286457041278482,
214
+ "epoch": 1.5555555555555556,
215
+ "grad_norm": 0.1009301245212555,
216
+ "learning_rate": 4.952013068883795e-05,
217
+ "loss": 0.1326,
218
+ "mean_token_accuracy": 0.9677493931353092,
219
+ "num_tokens": 7976360.0,
220
+ "step": 1050
221
+ },
222
+ {
223
+ "entropy": 0.13181614426895977,
224
+ "epoch": 1.6296296296296298,
225
+ "grad_norm": 0.09136403352022171,
226
+ "learning_rate": 4.5527138340828776e-05,
227
+ "loss": 0.1317,
228
+ "mean_token_accuracy": 0.9678143452107907,
229
+ "num_tokens": 8355146.0,
230
+ "step": 1100
231
+ },
232
+ {
233
+ "entropy": 0.12889527762308717,
234
+ "epoch": 1.7037037037037037,
235
+ "grad_norm": 0.11126290261745453,
236
+ "learning_rate": 4.156274235153189e-05,
237
+ "loss": 0.1289,
238
+ "mean_token_accuracy": 0.9681750671565532,
239
+ "num_tokens": 8736037.0,
240
+ "step": 1150
241
+ },
242
+ {
243
+ "entropy": 0.1293605554662645,
244
+ "epoch": 1.7777777777777777,
245
+ "grad_norm": 0.10993292182683945,
246
+ "learning_rate": 3.765228830469794e-05,
247
+ "loss": 0.1293,
248
+ "mean_token_accuracy": 0.9684934197366237,
249
+ "num_tokens": 9113158.0,
250
+ "step": 1200
251
+ },
252
+ {
253
+ "entropy": 0.12954492604359985,
254
+ "epoch": 1.8518518518518519,
255
+ "grad_norm": 0.1266999989748001,
256
+ "learning_rate": 3.3820776916908857e-05,
257
+ "loss": 0.1296,
258
+ "mean_token_accuracy": 0.9680785122513771,
259
+ "num_tokens": 9492245.0,
260
+ "step": 1250
261
+ },
262
+ {
263
+ "entropy": 0.13069430900737644,
264
+ "epoch": 1.925925925925926,
265
+ "grad_norm": 0.07351736724376678,
266
+ "learning_rate": 3.0092704200428058e-05,
267
+ "loss": 0.131,
268
+ "mean_token_accuracy": 0.9679618345201015,
269
+ "num_tokens": 9874560.0,
270
+ "step": 1300
271
+ },
272
+ {
273
+ "entropy": 0.12986605327576398,
274
+ "epoch": 2.0,
275
+ "grad_norm": 0.07602707296609879,
276
+ "learning_rate": 2.649190485277792e-05,
277
+ "loss": 0.1301,
278
+ "mean_token_accuracy": 0.9679882827401162,
279
+ "num_tokens": 10251446.0,
280
+ "step": 1350
281
+ },
282
+ {
283
+ "entropy": 0.13015099691227078,
284
+ "epoch": 2.074074074074074,
285
+ "grad_norm": 0.07422789186239243,
286
+ "learning_rate": 2.3041399874302905e-05,
287
+ "loss": 0.13,
288
+ "mean_token_accuracy": 0.968013653755188,
289
+ "num_tokens": 10637110.0,
290
+ "step": 1400
291
+ },
292
+ {
293
+ "entropy": 0.12833521047607063,
294
+ "epoch": 2.148148148148148,
295
+ "grad_norm": 0.06928899884223938,
296
+ "learning_rate": 1.976324938794482e-05,
297
+ "loss": 0.1287,
298
+ "mean_token_accuracy": 0.9684618780016899,
299
+ "num_tokens": 11014301.0,
300
+ "step": 1450
301
+ },
302
+ {
303
+ "entropy": 0.12765121564269066,
304
+ "epoch": 2.2222222222222223,
305
+ "grad_norm": 0.07737194001674652,
306
+ "learning_rate": 1.667841160219835e-05,
307
+ "loss": 0.1279,
308
+ "mean_token_accuracy": 0.9685468013584614,
309
+ "num_tokens": 11390895.0,
310
+ "step": 1500
311
+ }
312
+ ],
313
+ "logging_steps": 50,
314
+ "max_steps": 2025,
315
+ "num_input_tokens_seen": 0,
316
+ "num_train_epochs": 3,
317
+ "save_steps": 500,
318
+ "stateful_callbacks": {
319
+ "TrainerControl": {
320
+ "args": {
321
+ "should_epoch_stop": false,
322
+ "should_evaluate": false,
323
+ "should_log": false,
324
+ "should_save": true,
325
+ "should_training_stop": false
326
+ },
327
+ "attributes": {}
328
+ }
329
+ },
330
+ "total_flos": 4.7582808562861056e+17,
331
+ "train_batch_size": 1,
332
+ "trial_name": null,
333
+ "trial_params": null
334
+ }
checkpoint-1500/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:972906ac2311d1411092b921ffee2b39397b24618f8f2b157e1215061dd47de3
3
+ size 6225
checkpoint-1500/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2000/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: bigcode/starcoder2-7b
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:bigcode/starcoder2-7b
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 0.18.0
checkpoint-2000/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "bigcode/starcoder2-7b",
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": 32,
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": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "k_proj",
33
+ "v_proj",
34
+ "o_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": null,
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-2000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c060f7ff44fffee8513fedd3162490b8e59a2f529a3a884c6e94bf69e2fb2e89
3
+ size 58754616
checkpoint-2000/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:652cad21a5c363ec6c445384982fee8d2360575aeafd18ee7f5cf7b74551a53d
3
+ size 117660107
checkpoint-2000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4000c2a44fd7cc25b3279d9fbefe8605395fe301bc8c2967ffc5d3fe26845802
3
+ size 14645
checkpoint-2000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:591d55d90adc2dbaeabd46529428d7ba9aa1ba92348998be2f0a794eeb555bea
3
+ size 1465
checkpoint-2000/special_tokens_map.json ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|endoftext|>",
4
+ "<fim_prefix>",
5
+ "<fim_middle>",
6
+ "<fim_suffix>",
7
+ "<fim_pad>",
8
+ "<repo_name>",
9
+ "<file_sep>",
10
+ "<issue_start>",
11
+ "<issue_comment>",
12
+ "<issue_closed>",
13
+ "<jupyter_start>",
14
+ "<jupyter_text>",
15
+ "<jupyter_code>",
16
+ "<jupyter_output>",
17
+ "<jupyter_script>",
18
+ "<empty_output>",
19
+ "<code_to_intermediate>",
20
+ "<intermediate_to_code>",
21
+ "<pr>",
22
+ "<pr_status>",
23
+ "<pr_is_merged>",
24
+ "<pr_base>",
25
+ "<pr_file>",
26
+ "<pr_base_code>",
27
+ "<pr_diff>",
28
+ "<pr_diff_hunk>",
29
+ "<pr_comment>",
30
+ "<pr_event_id>",
31
+ "<pr_review>",
32
+ "<pr_review_state>",
33
+ "<pr_review_comment>",
34
+ "<pr_in_reply_to_review_id>",
35
+ "<pr_in_reply_to_comment_id>",
36
+ "<pr_diff_hunk_comment_line>",
37
+ "<NAME>",
38
+ "<EMAIL>",
39
+ "<KEY>",
40
+ "<PASSWORD>"
41
+ ],
42
+ "bos_token": {
43
+ "content": "<|endoftext|>",
44
+ "lstrip": false,
45
+ "normalized": false,
46
+ "rstrip": false,
47
+ "single_word": false
48
+ },
49
+ "eos_token": {
50
+ "content": "<|endoftext|>",
51
+ "lstrip": false,
52
+ "normalized": false,
53
+ "rstrip": false,
54
+ "single_word": false
55
+ },
56
+ "unk_token": {
57
+ "content": "<|endoftext|>",
58
+ "lstrip": false,
59
+ "normalized": false,
60
+ "rstrip": false,
61
+ "single_word": false
62
+ }
63
+ }
checkpoint-2000/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2000/tokenizer_config.json ADDED
@@ -0,0 +1,357 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "0": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "1": {
13
+ "content": "<fim_prefix>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "2": {
21
+ "content": "<fim_middle>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ },
28
+ "3": {
29
+ "content": "<fim_suffix>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
35
+ },
36
+ "4": {
37
+ "content": "<fim_pad>",
38
+ "lstrip": false,
39
+ "normalized": false,
40
+ "rstrip": false,
41
+ "single_word": false,
42
+ "special": true
43
+ },
44
+ "5": {
45
+ "content": "<repo_name>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
52
+ "6": {
53
+ "content": "<file_sep>",
54
+ "lstrip": false,
55
+ "normalized": false,
56
+ "rstrip": false,
57
+ "single_word": false,
58
+ "special": true
59
+ },
60
+ "7": {
61
+ "content": "<issue_start>",
62
+ "lstrip": false,
63
+ "normalized": false,
64
+ "rstrip": false,
65
+ "single_word": false,
66
+ "special": true
67
+ },
68
+ "8": {
69
+ "content": "<issue_comment>",
70
+ "lstrip": false,
71
+ "normalized": false,
72
+ "rstrip": false,
73
+ "single_word": false,
74
+ "special": true
75
+ },
76
+ "9": {
77
+ "content": "<issue_closed>",
78
+ "lstrip": false,
79
+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
82
+ "special": true
83
+ },
84
+ "10": {
85
+ "content": "<jupyter_start>",
86
+ "lstrip": false,
87
+ "normalized": false,
88
+ "rstrip": false,
89
+ "single_word": false,
90
+ "special": true
91
+ },
92
+ "11": {
93
+ "content": "<jupyter_text>",
94
+ "lstrip": false,
95
+ "normalized": false,
96
+ "rstrip": false,
97
+ "single_word": false,
98
+ "special": true
99
+ },
100
+ "12": {
101
+ "content": "<jupyter_code>",
102
+ "lstrip": false,
103
+ "normalized": false,
104
+ "rstrip": false,
105
+ "single_word": false,
106
+ "special": true
107
+ },
108
+ "13": {
109
+ "content": "<jupyter_output>",
110
+ "lstrip": false,
111
+ "normalized": false,
112
+ "rstrip": false,
113
+ "single_word": false,
114
+ "special": true
115
+ },
116
+ "14": {
117
+ "content": "<jupyter_script>",
118
+ "lstrip": false,
119
+ "normalized": false,
120
+ "rstrip": false,
121
+ "single_word": false,
122
+ "special": true
123
+ },
124
+ "15": {
125
+ "content": "<empty_output>",
126
+ "lstrip": false,
127
+ "normalized": false,
128
+ "rstrip": false,
129
+ "single_word": false,
130
+ "special": true
131
+ },
132
+ "16": {
133
+ "content": "<code_to_intermediate>",
134
+ "lstrip": false,
135
+ "normalized": false,
136
+ "rstrip": false,
137
+ "single_word": false,
138
+ "special": true
139
+ },
140
+ "17": {
141
+ "content": "<intermediate_to_code>",
142
+ "lstrip": false,
143
+ "normalized": false,
144
+ "rstrip": false,
145
+ "single_word": false,
146
+ "special": true
147
+ },
148
+ "18": {
149
+ "content": "<pr>",
150
+ "lstrip": false,
151
+ "normalized": false,
152
+ "rstrip": false,
153
+ "single_word": false,
154
+ "special": true
155
+ },
156
+ "19": {
157
+ "content": "<pr_status>",
158
+ "lstrip": false,
159
+ "normalized": false,
160
+ "rstrip": false,
161
+ "single_word": false,
162
+ "special": true
163
+ },
164
+ "20": {
165
+ "content": "<pr_is_merged>",
166
+ "lstrip": false,
167
+ "normalized": false,
168
+ "rstrip": false,
169
+ "single_word": false,
170
+ "special": true
171
+ },
172
+ "21": {
173
+ "content": "<pr_base>",
174
+ "lstrip": false,
175
+ "normalized": false,
176
+ "rstrip": false,
177
+ "single_word": false,
178
+ "special": true
179
+ },
180
+ "22": {
181
+ "content": "<pr_file>",
182
+ "lstrip": false,
183
+ "normalized": false,
184
+ "rstrip": false,
185
+ "single_word": false,
186
+ "special": true
187
+ },
188
+ "23": {
189
+ "content": "<pr_base_code>",
190
+ "lstrip": false,
191
+ "normalized": false,
192
+ "rstrip": false,
193
+ "single_word": false,
194
+ "special": true
195
+ },
196
+ "24": {
197
+ "content": "<pr_diff>",
198
+ "lstrip": false,
199
+ "normalized": false,
200
+ "rstrip": false,
201
+ "single_word": false,
202
+ "special": true
203
+ },
204
+ "25": {
205
+ "content": "<pr_diff_hunk>",
206
+ "lstrip": false,
207
+ "normalized": false,
208
+ "rstrip": false,
209
+ "single_word": false,
210
+ "special": true
211
+ },
212
+ "26": {
213
+ "content": "<pr_comment>",
214
+ "lstrip": false,
215
+ "normalized": false,
216
+ "rstrip": false,
217
+ "single_word": false,
218
+ "special": true
219
+ },
220
+ "27": {
221
+ "content": "<pr_event_id>",
222
+ "lstrip": false,
223
+ "normalized": false,
224
+ "rstrip": false,
225
+ "single_word": false,
226
+ "special": true
227
+ },
228
+ "28": {
229
+ "content": "<pr_review>",
230
+ "lstrip": false,
231
+ "normalized": false,
232
+ "rstrip": false,
233
+ "single_word": false,
234
+ "special": true
235
+ },
236
+ "29": {
237
+ "content": "<pr_review_state>",
238
+ "lstrip": false,
239
+ "normalized": false,
240
+ "rstrip": false,
241
+ "single_word": false,
242
+ "special": true
243
+ },
244
+ "30": {
245
+ "content": "<pr_review_comment>",
246
+ "lstrip": false,
247
+ "normalized": false,
248
+ "rstrip": false,
249
+ "single_word": false,
250
+ "special": true
251
+ },
252
+ "31": {
253
+ "content": "<pr_in_reply_to_review_id>",
254
+ "lstrip": false,
255
+ "normalized": false,
256
+ "rstrip": false,
257
+ "single_word": false,
258
+ "special": true
259
+ },
260
+ "32": {
261
+ "content": "<pr_in_reply_to_comment_id>",
262
+ "lstrip": false,
263
+ "normalized": false,
264
+ "rstrip": false,
265
+ "single_word": false,
266
+ "special": true
267
+ },
268
+ "33": {
269
+ "content": "<pr_diff_hunk_comment_line>",
270
+ "lstrip": false,
271
+ "normalized": false,
272
+ "rstrip": false,
273
+ "single_word": false,
274
+ "special": true
275
+ },
276
+ "34": {
277
+ "content": "<NAME>",
278
+ "lstrip": false,
279
+ "normalized": false,
280
+ "rstrip": false,
281
+ "single_word": false,
282
+ "special": true
283
+ },
284
+ "35": {
285
+ "content": "<EMAIL>",
286
+ "lstrip": false,
287
+ "normalized": false,
288
+ "rstrip": false,
289
+ "single_word": false,
290
+ "special": true
291
+ },
292
+ "36": {
293
+ "content": "<KEY>",
294
+ "lstrip": false,
295
+ "normalized": false,
296
+ "rstrip": false,
297
+ "single_word": false,
298
+ "special": true
299
+ },
300
+ "37": {
301
+ "content": "<PASSWORD>",
302
+ "lstrip": false,
303
+ "normalized": false,
304
+ "rstrip": false,
305
+ "single_word": false,
306
+ "special": true
307
+ }
308
+ },
309
+ "additional_special_tokens": [
310
+ "<|endoftext|>",
311
+ "<fim_prefix>",
312
+ "<fim_middle>",
313
+ "<fim_suffix>",
314
+ "<fim_pad>",
315
+ "<repo_name>",
316
+ "<file_sep>",
317
+ "<issue_start>",
318
+ "<issue_comment>",
319
+ "<issue_closed>",
320
+ "<jupyter_start>",
321
+ "<jupyter_text>",
322
+ "<jupyter_code>",
323
+ "<jupyter_output>",
324
+ "<jupyter_script>",
325
+ "<empty_output>",
326
+ "<code_to_intermediate>",
327
+ "<intermediate_to_code>",
328
+ "<pr>",
329
+ "<pr_status>",
330
+ "<pr_is_merged>",
331
+ "<pr_base>",
332
+ "<pr_file>",
333
+ "<pr_base_code>",
334
+ "<pr_diff>",
335
+ "<pr_diff_hunk>",
336
+ "<pr_comment>",
337
+ "<pr_event_id>",
338
+ "<pr_review>",
339
+ "<pr_review_state>",
340
+ "<pr_review_comment>",
341
+ "<pr_in_reply_to_review_id>",
342
+ "<pr_in_reply_to_comment_id>",
343
+ "<pr_diff_hunk_comment_line>",
344
+ "<NAME>",
345
+ "<EMAIL>",
346
+ "<KEY>",
347
+ "<PASSWORD>"
348
+ ],
349
+ "bos_token": "<|endoftext|>",
350
+ "clean_up_tokenization_spaces": true,
351
+ "eos_token": "<|endoftext|>",
352
+ "extra_special_tokens": {},
353
+ "model_max_length": 1000000000000000019884624838656,
354
+ "tokenizer_class": "GPT2Tokenizer",
355
+ "unk_token": "<|endoftext|>",
356
+ "vocab_size": 49152
357
+ }
checkpoint-2000/trainer_state.json ADDED
@@ -0,0 +1,434 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.962962962962963,
6
+ "eval_steps": 500,
7
+ "global_step": 2000,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.9540774886310102,
14
+ "epoch": 0.07407407407407407,
15
+ "grad_norm": 0.8241696953773499,
16
+ "learning_rate": 8.032786885245902e-05,
17
+ "loss": 1.7451,
18
+ "mean_token_accuracy": 0.6189013833552599,
19
+ "num_tokens": 379953.0,
20
+ "step": 50
21
+ },
22
+ {
23
+ "entropy": 0.5046265083923935,
24
+ "epoch": 0.14814814814814814,
25
+ "grad_norm": 4.424446105957031,
26
+ "learning_rate": 9.990765991730485e-05,
27
+ "loss": 0.4302,
28
+ "mean_token_accuracy": 0.8861582314968109,
29
+ "num_tokens": 757047.0,
30
+ "step": 100
31
+ },
32
+ {
33
+ "entropy": 0.24775007627904416,
34
+ "epoch": 0.2222222222222222,
35
+ "grad_norm": 0.30575165152549744,
36
+ "learning_rate": 9.950545603782162e-05,
37
+ "loss": 0.2323,
38
+ "mean_token_accuracy": 0.940535937026143,
39
+ "num_tokens": 1134378.0,
40
+ "step": 150
41
+ },
42
+ {
43
+ "entropy": 0.1925063591822982,
44
+ "epoch": 0.2962962962962963,
45
+ "grad_norm": 0.24072137475013733,
46
+ "learning_rate": 9.878674879048427e-05,
47
+ "loss": 0.1856,
48
+ "mean_token_accuracy": 0.9529062640666962,
49
+ "num_tokens": 1516152.0,
50
+ "step": 200
51
+ },
52
+ {
53
+ "entropy": 0.18322961997240783,
54
+ "epoch": 0.37037037037037035,
55
+ "grad_norm": 0.18854060769081116,
56
+ "learning_rate": 9.775613308830824e-05,
57
+ "loss": 0.1775,
58
+ "mean_token_accuracy": 0.9546041788160801,
59
+ "num_tokens": 1896494.0,
60
+ "step": 250
61
+ },
62
+ {
63
+ "entropy": 0.17187482433393597,
64
+ "epoch": 0.4444444444444444,
65
+ "grad_norm": 0.18019668757915497,
66
+ "learning_rate": 9.642019796948866e-05,
67
+ "loss": 0.164,
68
+ "mean_token_accuracy": 0.9579361644387245,
69
+ "num_tokens": 2277194.0,
70
+ "step": 300
71
+ },
72
+ {
73
+ "entropy": 0.16193925650790333,
74
+ "epoch": 0.5185185185185185,
75
+ "grad_norm": 0.23759332299232483,
76
+ "learning_rate": 9.478748447168449e-05,
77
+ "loss": 0.1539,
78
+ "mean_token_accuracy": 0.9614081564545631,
79
+ "num_tokens": 2658243.0,
80
+ "step": 350
81
+ },
82
+ {
83
+ "entropy": 0.15039873549714686,
84
+ "epoch": 0.5925925925925926,
85
+ "grad_norm": 0.2590758204460144,
86
+ "learning_rate": 9.28684310265789e-05,
87
+ "loss": 0.1443,
88
+ "mean_token_accuracy": 0.9650989197194576,
89
+ "num_tokens": 3041430.0,
90
+ "step": 400
91
+ },
92
+ {
93
+ "entropy": 0.14228019634261727,
94
+ "epoch": 0.6666666666666666,
95
+ "grad_norm": 0.18062612414360046,
96
+ "learning_rate": 9.067530672382544e-05,
97
+ "loss": 0.1366,
98
+ "mean_token_accuracy": 0.9667340110242367,
99
+ "num_tokens": 3422368.0,
100
+ "step": 450
101
+ },
102
+ {
103
+ "entropy": 0.1391275341436267,
104
+ "epoch": 0.7407407407407407,
105
+ "grad_norm": 0.1984509527683258,
106
+ "learning_rate": 8.822213287104348e-05,
107
+ "loss": 0.1352,
108
+ "mean_token_accuracy": 0.9674024738371372,
109
+ "num_tokens": 3801968.0,
110
+ "step": 500
111
+ },
112
+ {
113
+ "entropy": 0.13673329239711166,
114
+ "epoch": 0.8148148148148148,
115
+ "grad_norm": 0.13088534772396088,
116
+ "learning_rate": 8.552459335135381e-05,
117
+ "loss": 0.1354,
118
+ "mean_token_accuracy": 0.9673544447124004,
119
+ "num_tokens": 4182102.0,
120
+ "step": 550
121
+ },
122
+ {
123
+ "entropy": 0.13533455861732363,
124
+ "epoch": 0.8888888888888888,
125
+ "grad_norm": 0.33587542176246643,
126
+ "learning_rate": 8.259993435156559e-05,
127
+ "loss": 0.1325,
128
+ "mean_token_accuracy": 0.9676820485293866,
129
+ "num_tokens": 4561998.0,
130
+ "step": 600
131
+ },
132
+ {
133
+ "entropy": 0.13281562993302942,
134
+ "epoch": 0.9629629629629629,
135
+ "grad_norm": 0.11626797914505005,
136
+ "learning_rate": 7.946685410208296e-05,
137
+ "loss": 0.1313,
138
+ "mean_token_accuracy": 0.9678142921626568,
139
+ "num_tokens": 4936347.0,
140
+ "step": 650
141
+ },
142
+ {
143
+ "entropy": 0.1338025047816336,
144
+ "epoch": 1.037037037037037,
145
+ "grad_norm": 0.10883153975009918,
146
+ "learning_rate": 7.614538333345735e-05,
147
+ "loss": 0.1328,
148
+ "mean_token_accuracy": 0.9673172944784164,
149
+ "num_tokens": 5313396.0,
150
+ "step": 700
151
+ },
152
+ {
153
+ "entropy": 0.1330988533422351,
154
+ "epoch": 1.1111111111111112,
155
+ "grad_norm": 0.14333182573318481,
156
+ "learning_rate": 7.265675721386285e-05,
157
+ "loss": 0.1317,
158
+ "mean_token_accuracy": 0.9678454534709453,
159
+ "num_tokens": 5694821.0,
160
+ "step": 750
161
+ },
162
+ {
163
+ "entropy": 0.1315150342695415,
164
+ "epoch": 1.1851851851851851,
165
+ "grad_norm": 0.07893866300582886,
166
+ "learning_rate": 6.902327958623736e-05,
167
+ "loss": 0.131,
168
+ "mean_token_accuracy": 0.9678919970989227,
169
+ "num_tokens": 6071147.0,
170
+ "step": 800
171
+ },
172
+ {
173
+ "entropy": 0.1348141137883067,
174
+ "epoch": 1.2592592592592593,
175
+ "grad_norm": 0.10548827797174454,
176
+ "learning_rate": 6.526818037306228e-05,
177
+ "loss": 0.1337,
178
+ "mean_token_accuracy": 0.9671075843274594,
179
+ "num_tokens": 6454454.0,
180
+ "step": 850
181
+ },
182
+ {
183
+ "entropy": 0.12924523117020725,
184
+ "epoch": 1.3333333333333333,
185
+ "grad_norm": 0.13734276592731476,
186
+ "learning_rate": 6.14154670604355e-05,
187
+ "loss": 0.1294,
188
+ "mean_token_accuracy": 0.9686036820709706,
189
+ "num_tokens": 6831407.0,
190
+ "step": 900
191
+ },
192
+ {
193
+ "entropy": 0.13089272173121572,
194
+ "epoch": 1.4074074074074074,
195
+ "grad_norm": 0.062484513968229294,
196
+ "learning_rate": 5.7489771210944564e-05,
197
+ "loss": 0.1304,
198
+ "mean_token_accuracy": 0.9679886139929295,
199
+ "num_tokens": 7211253.0,
200
+ "step": 950
201
+ },
202
+ {
203
+ "entropy": 0.1295284123532474,
204
+ "epoch": 1.4814814814814814,
205
+ "grad_norm": 0.07434429228305817,
206
+ "learning_rate": 5.351619098663021e-05,
207
+ "loss": 0.1289,
208
+ "mean_token_accuracy": 0.9682336232066154,
209
+ "num_tokens": 7591172.0,
210
+ "step": 1000
211
+ },
212
+ {
213
+ "entropy": 0.13286457041278482,
214
+ "epoch": 1.5555555555555556,
215
+ "grad_norm": 0.1009301245212555,
216
+ "learning_rate": 4.952013068883795e-05,
217
+ "loss": 0.1326,
218
+ "mean_token_accuracy": 0.9677493931353092,
219
+ "num_tokens": 7976360.0,
220
+ "step": 1050
221
+ },
222
+ {
223
+ "entropy": 0.13181614426895977,
224
+ "epoch": 1.6296296296296298,
225
+ "grad_norm": 0.09136403352022171,
226
+ "learning_rate": 4.5527138340828776e-05,
227
+ "loss": 0.1317,
228
+ "mean_token_accuracy": 0.9678143452107907,
229
+ "num_tokens": 8355146.0,
230
+ "step": 1100
231
+ },
232
+ {
233
+ "entropy": 0.12889527762308717,
234
+ "epoch": 1.7037037037037037,
235
+ "grad_norm": 0.11126290261745453,
236
+ "learning_rate": 4.156274235153189e-05,
237
+ "loss": 0.1289,
238
+ "mean_token_accuracy": 0.9681750671565532,
239
+ "num_tokens": 8736037.0,
240
+ "step": 1150
241
+ },
242
+ {
243
+ "entropy": 0.1293605554662645,
244
+ "epoch": 1.7777777777777777,
245
+ "grad_norm": 0.10993292182683945,
246
+ "learning_rate": 3.765228830469794e-05,
247
+ "loss": 0.1293,
248
+ "mean_token_accuracy": 0.9684934197366237,
249
+ "num_tokens": 9113158.0,
250
+ "step": 1200
251
+ },
252
+ {
253
+ "entropy": 0.12954492604359985,
254
+ "epoch": 1.8518518518518519,
255
+ "grad_norm": 0.1266999989748001,
256
+ "learning_rate": 3.3820776916908857e-05,
257
+ "loss": 0.1296,
258
+ "mean_token_accuracy": 0.9680785122513771,
259
+ "num_tokens": 9492245.0,
260
+ "step": 1250
261
+ },
262
+ {
263
+ "entropy": 0.13069430900737644,
264
+ "epoch": 1.925925925925926,
265
+ "grad_norm": 0.07351736724376678,
266
+ "learning_rate": 3.0092704200428058e-05,
267
+ "loss": 0.131,
268
+ "mean_token_accuracy": 0.9679618345201015,
269
+ "num_tokens": 9874560.0,
270
+ "step": 1300
271
+ },
272
+ {
273
+ "entropy": 0.12986605327576398,
274
+ "epoch": 2.0,
275
+ "grad_norm": 0.07602707296609879,
276
+ "learning_rate": 2.649190485277792e-05,
277
+ "loss": 0.1301,
278
+ "mean_token_accuracy": 0.9679882827401162,
279
+ "num_tokens": 10251446.0,
280
+ "step": 1350
281
+ },
282
+ {
283
+ "entropy": 0.13015099691227078,
284
+ "epoch": 2.074074074074074,
285
+ "grad_norm": 0.07422789186239243,
286
+ "learning_rate": 2.3041399874302905e-05,
287
+ "loss": 0.13,
288
+ "mean_token_accuracy": 0.968013653755188,
289
+ "num_tokens": 10637110.0,
290
+ "step": 1400
291
+ },
292
+ {
293
+ "entropy": 0.12833521047607063,
294
+ "epoch": 2.148148148148148,
295
+ "grad_norm": 0.06928899884223938,
296
+ "learning_rate": 1.976324938794482e-05,
297
+ "loss": 0.1287,
298
+ "mean_token_accuracy": 0.9684618780016899,
299
+ "num_tokens": 11014301.0,
300
+ "step": 1450
301
+ },
302
+ {
303
+ "entropy": 0.12765121564269066,
304
+ "epoch": 2.2222222222222223,
305
+ "grad_norm": 0.07737194001674652,
306
+ "learning_rate": 1.667841160219835e-05,
307
+ "loss": 0.1279,
308
+ "mean_token_accuracy": 0.9685468013584614,
309
+ "num_tokens": 11390895.0,
310
+ "step": 1500
311
+ },
312
+ {
313
+ "entropy": 0.13076237022876738,
314
+ "epoch": 2.2962962962962963,
315
+ "grad_norm": 0.0690469890832901,
316
+ "learning_rate": 1.3806608818939203e-05,
317
+ "loss": 0.1308,
318
+ "mean_token_accuracy": 0.9680638153851032,
319
+ "num_tokens": 11773360.0,
320
+ "step": 1550
321
+ },
322
+ {
323
+ "entropy": 0.1271959487348795,
324
+ "epoch": 2.3703703703703702,
325
+ "grad_norm": 0.08058126270771027,
326
+ "learning_rate": 1.1166201342777438e-05,
327
+ "loss": 0.1275,
328
+ "mean_token_accuracy": 0.9684904217720032,
329
+ "num_tokens": 12152692.0,
330
+ "step": 1600
331
+ },
332
+ {
333
+ "entropy": 0.12783636916428803,
334
+ "epoch": 2.4444444444444446,
335
+ "grad_norm": 0.08844149112701416,
336
+ "learning_rate": 8.774070098071668e-06,
337
+ "loss": 0.1278,
338
+ "mean_token_accuracy": 0.9686374716460705,
339
+ "num_tokens": 12532074.0,
340
+ "step": 1650
341
+ },
342
+ {
343
+ "entropy": 0.12949045987799765,
344
+ "epoch": 2.5185185185185186,
345
+ "grad_norm": 0.0735594779253006,
346
+ "learning_rate": 6.645508704069003e-06,
347
+ "loss": 0.13,
348
+ "mean_token_accuracy": 0.9678716999292374,
349
+ "num_tokens": 12914270.0,
350
+ "step": 1700
351
+ },
352
+ {
353
+ "entropy": 0.12908031923696398,
354
+ "epoch": 2.5925925925925926,
355
+ "grad_norm": 0.0713183730840683,
356
+ "learning_rate": 4.794125698167262e-06,
357
+ "loss": 0.1291,
358
+ "mean_token_accuracy": 0.9681964771449566,
359
+ "num_tokens": 13293683.0,
360
+ "step": 1750
361
+ },
362
+ {
363
+ "entropy": 0.12857461655512453,
364
+ "epoch": 2.6666666666666665,
365
+ "grad_norm": 0.06526947021484375,
366
+ "learning_rate": 3.231757532415458e-06,
367
+ "loss": 0.1287,
368
+ "mean_token_accuracy": 0.9684041538834571,
369
+ "num_tokens": 13671470.0,
370
+ "step": 1800
371
+ },
372
+ {
373
+ "entropy": 0.12981407037004827,
374
+ "epoch": 2.7407407407407405,
375
+ "grad_norm": 0.06781283766031265,
376
+ "learning_rate": 1.9683928994924385e-06,
377
+ "loss": 0.1304,
378
+ "mean_token_accuracy": 0.9678549686074257,
379
+ "num_tokens": 14051413.0,
380
+ "step": 1850
381
+ },
382
+ {
383
+ "entropy": 0.1281242691539228,
384
+ "epoch": 2.814814814814815,
385
+ "grad_norm": 0.06520246714353561,
386
+ "learning_rate": 1.0121088719706296e-06,
387
+ "loss": 0.1291,
388
+ "mean_token_accuracy": 0.968293984234333,
389
+ "num_tokens": 14429791.0,
390
+ "step": 1900
391
+ },
392
+ {
393
+ "entropy": 0.12915834257379175,
394
+ "epoch": 2.888888888888889,
395
+ "grad_norm": 0.07606221735477448,
396
+ "learning_rate": 3.6901926314575894e-07,
397
+ "loss": 0.1292,
398
+ "mean_token_accuracy": 0.9681269869208335,
399
+ "num_tokens": 14808357.0,
400
+ "step": 1950
401
+ },
402
+ {
403
+ "entropy": 0.1287903120368719,
404
+ "epoch": 2.962962962962963,
405
+ "grad_norm": 0.07113504409790039,
406
+ "learning_rate": 4.323553957759629e-08,
407
+ "loss": 0.1286,
408
+ "mean_token_accuracy": 0.9684909208118916,
409
+ "num_tokens": 15187872.0,
410
+ "step": 2000
411
+ }
412
+ ],
413
+ "logging_steps": 50,
414
+ "max_steps": 2025,
415
+ "num_input_tokens_seen": 0,
416
+ "num_train_epochs": 3,
417
+ "save_steps": 500,
418
+ "stateful_callbacks": {
419
+ "TrainerControl": {
420
+ "args": {
421
+ "should_epoch_stop": false,
422
+ "should_evaluate": false,
423
+ "should_log": false,
424
+ "should_save": true,
425
+ "should_training_stop": false
426
+ },
427
+ "attributes": {}
428
+ }
429
+ },
430
+ "total_flos": 6.344379487768412e+17,
431
+ "train_batch_size": 1,
432
+ "trial_name": null,
433
+ "trial_params": null
434
+ }
checkpoint-2000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:972906ac2311d1411092b921ffee2b39397b24618f8f2b157e1215061dd47de3
3
+ size 6225
checkpoint-2000/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2025/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: bigcode/starcoder2-7b
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:bigcode/starcoder2-7b
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 0.18.0
checkpoint-2025/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "bigcode/starcoder2-7b",
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": 32,
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": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "k_proj",
33
+ "v_proj",
34
+ "o_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": null,
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-2025/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:107a991d7b01bf7d71ef4cde195d1e9daed9f702aae4e7c7a7808aa7fb567d21
3
+ size 58754616
checkpoint-2025/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2025/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1b9a3260ade37aaf49929ec61c78757e669bda4186100d78c40fd8b6bc78abb2
3
+ size 117660107
checkpoint-2025/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b5c01deba5c6d17160913f300c88cd47225dadf938c7d775726c89149f6a055
3
+ size 14645
checkpoint-2025/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:24e77c94e08fe995eb38321a73baf050cd174cc938ef4133784c892be1db9c05
3
+ size 1465