agu18dec commited on
Commit
2d29b9b
·
verified ·
1 Parent(s): c9ab9cf

add checkpoint otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +11 -0
  2. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/README.md +61 -0
  3. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/adapter_config.json +48 -0
  4. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/adapter_model.safetensors +3 -0
  5. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/added_tokens.json +3 -0
  6. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/chat_template.jinja +47 -0
  7. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/README.md +209 -0
  8. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/adapter_config.json +48 -0
  9. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/adapter_model.safetensors +3 -0
  10. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/added_tokens.json +3 -0
  11. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/chat_template.jinja +47 -0
  12. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/preprocessor_config.json +29 -0
  13. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/processor_config.json +4 -0
  14. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/special_tokens_map.json +33 -0
  15. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer.json +3 -0
  16. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer.model +3 -0
  17. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer_config.json +0 -0
  18. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/trainer_state.json +0 -0
  19. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/training_args.bin +3 -0
  20. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/README.md +209 -0
  21. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/adapter_config.json +48 -0
  22. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/adapter_model.safetensors +3 -0
  23. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/added_tokens.json +3 -0
  24. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/chat_template.jinja +47 -0
  25. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/preprocessor_config.json +29 -0
  26. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/processor_config.json +4 -0
  27. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/special_tokens_map.json +33 -0
  28. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer.json +3 -0
  29. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer.model +3 -0
  30. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer_config.json +0 -0
  31. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/trainer_state.json +0 -0
  32. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/training_args.bin +3 -0
  33. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/README.md +209 -0
  34. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/adapter_config.json +48 -0
  35. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/adapter_model.safetensors +3 -0
  36. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/added_tokens.json +3 -0
  37. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/chat_template.jinja +47 -0
  38. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/preprocessor_config.json +29 -0
  39. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/processor_config.json +4 -0
  40. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/special_tokens_map.json +33 -0
  41. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer.json +3 -0
  42. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer.model +3 -0
  43. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer_config.json +0 -0
  44. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/trainer_state.json +1284 -0
  45. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/training_args.bin +3 -0
  46. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/README.md +209 -0
  47. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/adapter_config.json +48 -0
  48. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/adapter_model.safetensors +3 -0
  49. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/added_tokens.json +3 -0
  50. checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/chat_template.jinja +47 -0
.gitattributes CHANGED
@@ -382,3 +382,14 @@ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/checkpoint-6250/
382
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/checkpoint-7500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
383
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/checkpoint-8750/tokenizer.json filter=lfs diff=lfs merge=lfs -text
384
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
382
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/checkpoint-7500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
383
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/checkpoint-8750/tokenizer.json filter=lfs diff=lfs merge=lfs -text
384
  checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s2_baseline/tokenizer.json filter=lfs diff=lfs merge=lfs -text
385
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
386
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer.json filter=lfs diff=lfs merge=lfs -text
387
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer.json filter=lfs diff=lfs merge=lfs -text
388
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
389
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-2500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
390
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-3750/tokenizer.json filter=lfs diff=lfs merge=lfs -text
391
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-5000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
392
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-6250/tokenizer.json filter=lfs diff=lfs merge=lfs -text
393
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-7500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
394
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-8750/tokenizer.json filter=lfs diff=lfs merge=lfs -text
395
+ checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/tokenizer.json filter=lfs diff=lfs merge=lfs -text
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/README.md ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ model_name: otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline
5
+ tags:
6
+ - base_model:adapter:google/gemma-3-4b-it
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ licence: license
12
+ pipeline_tag: text-generation
13
+ ---
14
+
15
+ # Model Card for otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline
16
+
17
+ This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it).
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
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/agam-research/huggingface/runs/byv5l5w7)
34
+
35
+
36
+ This model was trained with SFT.
37
+
38
+ ### Framework versions
39
+
40
+ - PEFT 0.19.1
41
+ - TRL: 0.28.0
42
+ - Transformers: 4.57.6
43
+ - Pytorch: 2.9.1
44
+ - Datasets: 4.5.0
45
+ - Tokenizers: 0.22.2
46
+
47
+ ## Citations
48
+
49
+
50
+
51
+ Cite TRL as:
52
+
53
+ ```bibtex
54
+ @software{vonwerra2020trl,
55
+ title = {{TRL: Transformers Reinforcement Learning}},
56
+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
57
+ license = {Apache-2.0},
58
+ url = {https://github.com/huggingface/trl},
59
+ year = {2020}
60
+ }
61
+ ```
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "google/gemma-3-4b-it",
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": 0.0,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 8,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "down_proj",
34
+ "gate_proj",
35
+ "o_proj",
36
+ "k_proj",
37
+ "up_proj",
38
+ "v_proj",
39
+ "q_proj"
40
+ ],
41
+ "target_parameters": null,
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bb70dcda4b42fd284f3a34794b8278f4ecb4d143e214d35a922517e5cff749e6
3
+ size 65674128
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:google/gemma-3-4b-it
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 0.19.1
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "google/gemma-3-4b-it",
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": 0.0,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 8,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "down_proj",
34
+ "gate_proj",
35
+ "o_proj",
36
+ "k_proj",
37
+ "up_proj",
38
+ "v_proj",
39
+ "q_proj"
40
+ ],
41
+ "target_parameters": null,
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:17e1fee558d19cd4a85f315d65639fef9378acf4e913c092402ae56d721142b5
3
+ size 65674128
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<eos>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-10000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b25b8d8cffd67ea351659b350427764e9a6dcc4d1f692fe42a9968c21bd1cc6
3
+ size 6417
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:google/gemma-3-4b-it
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 0.19.1
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "google/gemma-3-4b-it",
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": 0.0,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 8,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "down_proj",
34
+ "gate_proj",
35
+ "o_proj",
36
+ "k_proj",
37
+ "up_proj",
38
+ "v_proj",
39
+ "q_proj"
40
+ ],
41
+ "target_parameters": null,
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ebf28306f055adc5a30bba39695813a9244199947770236f5685a06b4c77062
3
+ size 65674128
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<eos>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-11250/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b25b8d8cffd67ea351659b350427764e9a6dcc4d1f692fe42a9968c21bd1cc6
3
+ size 6417
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:google/gemma-3-4b-it
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 0.19.1
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "google/gemma-3-4b-it",
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": 0.0,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 8,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "down_proj",
34
+ "gate_proj",
35
+ "o_proj",
36
+ "k_proj",
37
+ "up_proj",
38
+ "v_proj",
39
+ "q_proj"
40
+ ],
41
+ "target_parameters": null,
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:371a515c36314e7cb665e296701075657197f9b4f555bb915c16308f987c82db
3
+ size 65674128
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": null,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<eos>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/trainer_state.json ADDED
@@ -0,0 +1,1284 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.0,
6
+ "eval_steps": 500,
7
+ "global_step": 1250,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 0.6517447352409362,
14
+ "epoch": 0.008,
15
+ "grad_norm": 13.304323196411133,
16
+ "learning_rate": 1.44e-06,
17
+ "loss": 1.2051,
18
+ "mean_token_accuracy": 0.7518506407737732,
19
+ "num_tokens": 10055.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 0.6488827526569366,
24
+ "epoch": 0.016,
25
+ "grad_norm": 14.009625434875488,
26
+ "learning_rate": 3.04e-06,
27
+ "loss": 1.1682,
28
+ "mean_token_accuracy": 0.7532002747058868,
29
+ "num_tokens": 19963.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 0.6849160015583038,
34
+ "epoch": 0.024,
35
+ "grad_norm": 14.544610023498535,
36
+ "learning_rate": 4.64e-06,
37
+ "loss": 1.0825,
38
+ "mean_token_accuracy": 0.7331112623214722,
39
+ "num_tokens": 30054.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 0.6808853566646575,
44
+ "epoch": 0.032,
45
+ "grad_norm": 10.353639602661133,
46
+ "learning_rate": 6.24e-06,
47
+ "loss": 0.7754,
48
+ "mean_token_accuracy": 0.7654528617858887,
49
+ "num_tokens": 39938.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 0.7086315333843232,
54
+ "epoch": 0.04,
55
+ "grad_norm": 7.067413806915283,
56
+ "learning_rate": 7.84e-06,
57
+ "loss": 0.5946,
58
+ "mean_token_accuracy": 0.8002863466739655,
59
+ "num_tokens": 50166.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 0.7584897458553315,
64
+ "epoch": 0.048,
65
+ "grad_norm": 5.474998950958252,
66
+ "learning_rate": 9.44e-06,
67
+ "loss": 0.6412,
68
+ "mean_token_accuracy": 0.7837531447410584,
69
+ "num_tokens": 60059.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 0.7520301103591919,
74
+ "epoch": 0.056,
75
+ "grad_norm": 4.642393112182617,
76
+ "learning_rate": 1.1040000000000001e-05,
77
+ "loss": 0.5667,
78
+ "mean_token_accuracy": 0.8009410679340363,
79
+ "num_tokens": 70143.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 0.7466191172599792,
84
+ "epoch": 0.064,
85
+ "grad_norm": 6.564879894256592,
86
+ "learning_rate": 1.2640000000000003e-05,
87
+ "loss": 0.562,
88
+ "mean_token_accuracy": 0.8044180452823639,
89
+ "num_tokens": 80014.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 0.737699156999588,
94
+ "epoch": 0.072,
95
+ "grad_norm": 5.0010881423950195,
96
+ "learning_rate": 1.4240000000000001e-05,
97
+ "loss": 0.5172,
98
+ "mean_token_accuracy": 0.8152086019515992,
99
+ "num_tokens": 90095.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 0.7431365609169006,
104
+ "epoch": 0.08,
105
+ "grad_norm": 5.928659439086914,
106
+ "learning_rate": 1.584e-05,
107
+ "loss": 0.5221,
108
+ "mean_token_accuracy": 0.8172156095504761,
109
+ "num_tokens": 100362.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 0.7396394312381744,
114
+ "epoch": 0.088,
115
+ "grad_norm": 4.8456950187683105,
116
+ "learning_rate": 1.7440000000000002e-05,
117
+ "loss": 0.5085,
118
+ "mean_token_accuracy": 0.8155511736869812,
119
+ "num_tokens": 110373.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 0.7305532455444336,
124
+ "epoch": 0.096,
125
+ "grad_norm": 5.342586040496826,
126
+ "learning_rate": 1.904e-05,
127
+ "loss": 0.473,
128
+ "mean_token_accuracy": 0.8297189176082611,
129
+ "num_tokens": 120330.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 0.7010469496250152,
134
+ "epoch": 0.104,
135
+ "grad_norm": 4.477506637573242,
136
+ "learning_rate": 2.0640000000000002e-05,
137
+ "loss": 0.4808,
138
+ "mean_token_accuracy": 0.8355620563030243,
139
+ "num_tokens": 130258.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 0.7325722575187683,
144
+ "epoch": 0.112,
145
+ "grad_norm": 5.776942253112793,
146
+ "learning_rate": 2.224e-05,
147
+ "loss": 0.4747,
148
+ "mean_token_accuracy": 0.8217672824859619,
149
+ "num_tokens": 140436.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 0.7283274173736572,
154
+ "epoch": 0.12,
155
+ "grad_norm": 4.776106834411621,
156
+ "learning_rate": 2.3840000000000002e-05,
157
+ "loss": 0.4878,
158
+ "mean_token_accuracy": 0.8249702036380768,
159
+ "num_tokens": 150558.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 0.7461902379989624,
164
+ "epoch": 0.128,
165
+ "grad_norm": 5.491858959197998,
166
+ "learning_rate": 2.5440000000000004e-05,
167
+ "loss": 0.5055,
168
+ "mean_token_accuracy": 0.8181215822696686,
169
+ "num_tokens": 160454.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 0.7387523293495178,
174
+ "epoch": 0.136,
175
+ "grad_norm": 4.031186103820801,
176
+ "learning_rate": 2.704e-05,
177
+ "loss": 0.4892,
178
+ "mean_token_accuracy": 0.8191783010959626,
179
+ "num_tokens": 170479.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 0.7172978222370148,
184
+ "epoch": 0.144,
185
+ "grad_norm": 4.5944061279296875,
186
+ "learning_rate": 2.864e-05,
187
+ "loss": 0.4381,
188
+ "mean_token_accuracy": 0.8387054204940796,
189
+ "num_tokens": 180442.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 0.711635684967041,
194
+ "epoch": 0.152,
195
+ "grad_norm": 3.530456066131592,
196
+ "learning_rate": 3.0240000000000002e-05,
197
+ "loss": 0.4265,
198
+ "mean_token_accuracy": 0.8430639147758484,
199
+ "num_tokens": 190507.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 0.7339554727077484,
204
+ "epoch": 0.16,
205
+ "grad_norm": 3.645368814468384,
206
+ "learning_rate": 3.184e-05,
207
+ "loss": 0.465,
208
+ "mean_token_accuracy": 0.8289207279682159,
209
+ "num_tokens": 200508.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 0.7236140966415405,
214
+ "epoch": 0.168,
215
+ "grad_norm": 4.230995178222656,
216
+ "learning_rate": 3.344e-05,
217
+ "loss": 0.4398,
218
+ "mean_token_accuracy": 0.8397033035755157,
219
+ "num_tokens": 210394.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 0.7196837246418,
224
+ "epoch": 0.176,
225
+ "grad_norm": 3.253856897354126,
226
+ "learning_rate": 3.504e-05,
227
+ "loss": 0.4359,
228
+ "mean_token_accuracy": 0.840765792131424,
229
+ "num_tokens": 220420.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 0.7125779867172242,
234
+ "epoch": 0.184,
235
+ "grad_norm": 4.0387163162231445,
236
+ "learning_rate": 3.664e-05,
237
+ "loss": 0.4118,
238
+ "mean_token_accuracy": 0.8490993976593018,
239
+ "num_tokens": 230359.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 0.724159049987793,
244
+ "epoch": 0.192,
245
+ "grad_norm": 3.5710225105285645,
246
+ "learning_rate": 3.8240000000000007e-05,
247
+ "loss": 0.4602,
248
+ "mean_token_accuracy": 0.8292092382907867,
249
+ "num_tokens": 240142.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 0.7112815618515015,
254
+ "epoch": 0.2,
255
+ "grad_norm": 4.761449337005615,
256
+ "learning_rate": 3.984e-05,
257
+ "loss": 0.4411,
258
+ "mean_token_accuracy": 0.8410702764987945,
259
+ "num_tokens": 250381.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 0.7280168414115906,
264
+ "epoch": 0.208,
265
+ "grad_norm": 3.5113282203674316,
266
+ "learning_rate": 4.144e-05,
267
+ "loss": 0.4277,
268
+ "mean_token_accuracy": 0.8378039479255677,
269
+ "num_tokens": 260388.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 0.715729832649231,
274
+ "epoch": 0.216,
275
+ "grad_norm": 3.883734703063965,
276
+ "learning_rate": 4.304e-05,
277
+ "loss": 0.4467,
278
+ "mean_token_accuracy": 0.8387612402439117,
279
+ "num_tokens": 270483.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 0.6883831679821014,
284
+ "epoch": 0.224,
285
+ "grad_norm": 3.4563710689544678,
286
+ "learning_rate": 4.4640000000000006e-05,
287
+ "loss": 0.3854,
288
+ "mean_token_accuracy": 0.8561008334159851,
289
+ "num_tokens": 280550.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 0.7114541232585907,
294
+ "epoch": 0.232,
295
+ "grad_norm": 4.078945636749268,
296
+ "learning_rate": 4.624e-05,
297
+ "loss": 0.4239,
298
+ "mean_token_accuracy": 0.8356595575809479,
299
+ "num_tokens": 290635.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 0.7148261308670044,
304
+ "epoch": 0.24,
305
+ "grad_norm": 4.1704840660095215,
306
+ "learning_rate": 4.784e-05,
307
+ "loss": 0.4053,
308
+ "mean_token_accuracy": 0.8485374748706818,
309
+ "num_tokens": 300716.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 0.6976641476154327,
314
+ "epoch": 0.248,
315
+ "grad_norm": 6.769944190979004,
316
+ "learning_rate": 4.944e-05,
317
+ "loss": 0.4463,
318
+ "mean_token_accuracy": 0.8296632826328277,
319
+ "num_tokens": 310763.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 0.7336399972438812,
324
+ "epoch": 0.256,
325
+ "grad_norm": 3.4586522579193115,
326
+ "learning_rate": 5.104e-05,
327
+ "loss": 0.428,
328
+ "mean_token_accuracy": 0.839785122871399,
329
+ "num_tokens": 320739.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 0.7039563238620759,
334
+ "epoch": 0.264,
335
+ "grad_norm": 4.9698591232299805,
336
+ "learning_rate": 5.264e-05,
337
+ "loss": 0.3886,
338
+ "mean_token_accuracy": 0.8518033504486084,
339
+ "num_tokens": 330765.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 0.7286165356636047,
344
+ "epoch": 0.272,
345
+ "grad_norm": 4.455258369445801,
346
+ "learning_rate": 5.424e-05,
347
+ "loss": 0.4379,
348
+ "mean_token_accuracy": 0.8310850203037262,
349
+ "num_tokens": 340774.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 0.7566006064414978,
354
+ "epoch": 0.28,
355
+ "grad_norm": 3.1348392963409424,
356
+ "learning_rate": 5.584e-05,
357
+ "loss": 0.4275,
358
+ "mean_token_accuracy": 0.8401350796222686,
359
+ "num_tokens": 350950.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 0.7498272895812989,
364
+ "epoch": 0.288,
365
+ "grad_norm": 4.724481582641602,
366
+ "learning_rate": 5.7440000000000006e-05,
367
+ "loss": 0.4217,
368
+ "mean_token_accuracy": 0.8399569928646088,
369
+ "num_tokens": 361030.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 0.7364974081516266,
374
+ "epoch": 0.296,
375
+ "grad_norm": 4.332886695861816,
376
+ "learning_rate": 5.9040000000000004e-05,
377
+ "loss": 0.3882,
378
+ "mean_token_accuracy": 0.8492311537265778,
379
+ "num_tokens": 371103.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 0.7401327073574067,
384
+ "epoch": 0.304,
385
+ "grad_norm": 3.2729179859161377,
386
+ "learning_rate": 6.064000000000001e-05,
387
+ "loss": 0.4078,
388
+ "mean_token_accuracy": 0.8473742246627808,
389
+ "num_tokens": 381221.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 0.7454682946205139,
394
+ "epoch": 0.312,
395
+ "grad_norm": 4.101840972900391,
396
+ "learning_rate": 6.224e-05,
397
+ "loss": 0.3827,
398
+ "mean_token_accuracy": 0.8516541600227356,
399
+ "num_tokens": 391401.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 0.7540267109870911,
404
+ "epoch": 0.32,
405
+ "grad_norm": 4.584408760070801,
406
+ "learning_rate": 6.384e-05,
407
+ "loss": 0.3883,
408
+ "mean_token_accuracy": 0.8520707130432129,
409
+ "num_tokens": 401517.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 0.7678898334503174,
414
+ "epoch": 0.328,
415
+ "grad_norm": 3.7839274406433105,
416
+ "learning_rate": 6.544e-05,
417
+ "loss": 0.4136,
418
+ "mean_token_accuracy": 0.8492289066314698,
419
+ "num_tokens": 411527.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 0.75483837723732,
424
+ "epoch": 0.336,
425
+ "grad_norm": 3.7808070182800293,
426
+ "learning_rate": 6.704000000000001e-05,
427
+ "loss": 0.3864,
428
+ "mean_token_accuracy": 0.8533409416675568,
429
+ "num_tokens": 421379.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 0.7809491693973541,
434
+ "epoch": 0.344,
435
+ "grad_norm": 4.6651201248168945,
436
+ "learning_rate": 6.864000000000001e-05,
437
+ "loss": 0.4003,
438
+ "mean_token_accuracy": 0.8476006865501404,
439
+ "num_tokens": 431499.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 0.7637096405029297,
444
+ "epoch": 0.352,
445
+ "grad_norm": 3.700791597366333,
446
+ "learning_rate": 7.024e-05,
447
+ "loss": 0.4135,
448
+ "mean_token_accuracy": 0.8419409990310669,
449
+ "num_tokens": 441544.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 0.7409621119499207,
454
+ "epoch": 0.36,
455
+ "grad_norm": 4.35798978805542,
456
+ "learning_rate": 7.184e-05,
457
+ "loss": 0.3577,
458
+ "mean_token_accuracy": 0.8639594912528992,
459
+ "num_tokens": 451566.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 0.743074893951416,
464
+ "epoch": 0.368,
465
+ "grad_norm": 3.672800064086914,
466
+ "learning_rate": 7.344000000000002e-05,
467
+ "loss": 0.3981,
468
+ "mean_token_accuracy": 0.854806250333786,
469
+ "num_tokens": 461625.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 0.7390820384025574,
474
+ "epoch": 0.376,
475
+ "grad_norm": 4.984609603881836,
476
+ "learning_rate": 7.504e-05,
477
+ "loss": 0.4038,
478
+ "mean_token_accuracy": 0.849916672706604,
479
+ "num_tokens": 471667.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 0.7496122181415558,
484
+ "epoch": 0.384,
485
+ "grad_norm": 3.7070982456207275,
486
+ "learning_rate": 7.664e-05,
487
+ "loss": 0.364,
488
+ "mean_token_accuracy": 0.8587370991706849,
489
+ "num_tokens": 481767.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 0.7406512439250946,
494
+ "epoch": 0.392,
495
+ "grad_norm": 4.055230617523193,
496
+ "learning_rate": 7.824e-05,
497
+ "loss": 0.3866,
498
+ "mean_token_accuracy": 0.853862851858139,
499
+ "num_tokens": 491859.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 0.6691052734851837,
504
+ "epoch": 0.4,
505
+ "grad_norm": 6.206707000732422,
506
+ "learning_rate": 7.984000000000001e-05,
507
+ "loss": 0.3584,
508
+ "mean_token_accuracy": 0.8651340901851654,
509
+ "num_tokens": 502103.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 0.7127264261245727,
514
+ "epoch": 0.408,
515
+ "grad_norm": 2.857799530029297,
516
+ "learning_rate": 8.144e-05,
517
+ "loss": 0.3749,
518
+ "mean_token_accuracy": 0.8569707155227662,
519
+ "num_tokens": 512215.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 0.6989680230617523,
524
+ "epoch": 0.416,
525
+ "grad_norm": 3.7977161407470703,
526
+ "learning_rate": 8.304e-05,
527
+ "loss": 0.3696,
528
+ "mean_token_accuracy": 0.862414437532425,
529
+ "num_tokens": 522207.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 0.7255340337753295,
534
+ "epoch": 0.424,
535
+ "grad_norm": 2.523075580596924,
536
+ "learning_rate": 8.464e-05,
537
+ "loss": 0.3501,
538
+ "mean_token_accuracy": 0.8673852860927582,
539
+ "num_tokens": 532139.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 0.7114777028560638,
544
+ "epoch": 0.432,
545
+ "grad_norm": 3.5952746868133545,
546
+ "learning_rate": 8.624000000000001e-05,
547
+ "loss": 0.3632,
548
+ "mean_token_accuracy": 0.8614569187164307,
549
+ "num_tokens": 542125.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 0.749547004699707,
554
+ "epoch": 0.44,
555
+ "grad_norm": 4.453001976013184,
556
+ "learning_rate": 8.784e-05,
557
+ "loss": 0.3985,
558
+ "mean_token_accuracy": 0.8507158756256104,
559
+ "num_tokens": 552410.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 0.7473198175430298,
564
+ "epoch": 0.448,
565
+ "grad_norm": 3.6924071311950684,
566
+ "learning_rate": 8.944e-05,
567
+ "loss": 0.3995,
568
+ "mean_token_accuracy": 0.8486853897571563,
569
+ "num_tokens": 562606.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 0.711093932390213,
574
+ "epoch": 0.456,
575
+ "grad_norm": 3.1549296379089355,
576
+ "learning_rate": 9.104000000000001e-05,
577
+ "loss": 0.3878,
578
+ "mean_token_accuracy": 0.8508474111557007,
579
+ "num_tokens": 572537.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 0.7114456057548523,
584
+ "epoch": 0.464,
585
+ "grad_norm": 3.332331657409668,
586
+ "learning_rate": 9.264000000000001e-05,
587
+ "loss": 0.3725,
588
+ "mean_token_accuracy": 0.8580802261829377,
589
+ "num_tokens": 582661.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 0.7008551478385925,
594
+ "epoch": 0.472,
595
+ "grad_norm": 4.147095203399658,
596
+ "learning_rate": 9.424e-05,
597
+ "loss": 0.3391,
598
+ "mean_token_accuracy": 0.870452344417572,
599
+ "num_tokens": 592642.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 0.7253452599048614,
604
+ "epoch": 0.48,
605
+ "grad_norm": 4.314738750457764,
606
+ "learning_rate": 9.584e-05,
607
+ "loss": 0.3666,
608
+ "mean_token_accuracy": 0.8685142874717713,
609
+ "num_tokens": 602797.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 0.7198026478290558,
614
+ "epoch": 0.488,
615
+ "grad_norm": 3.4705069065093994,
616
+ "learning_rate": 9.744000000000002e-05,
617
+ "loss": 0.3458,
618
+ "mean_token_accuracy": 0.8706252574920654,
619
+ "num_tokens": 612563.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 0.750393933057785,
624
+ "epoch": 0.496,
625
+ "grad_norm": 3.8125782012939453,
626
+ "learning_rate": 9.904e-05,
627
+ "loss": 0.3761,
628
+ "mean_token_accuracy": 0.8550220787525177,
629
+ "num_tokens": 622605.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 0.769760149717331,
634
+ "epoch": 0.504,
635
+ "grad_norm": 4.06261682510376,
636
+ "learning_rate": 9.999997200422726e-05,
637
+ "loss": 0.4081,
638
+ "mean_token_accuracy": 0.841312825679779,
639
+ "num_tokens": 632493.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 0.7663174033164978,
644
+ "epoch": 0.512,
645
+ "grad_norm": 3.6885271072387695,
646
+ "learning_rate": 9.999965705214383e-05,
647
+ "loss": 0.3844,
648
+ "mean_token_accuracy": 0.8508110165596008,
649
+ "num_tokens": 642455.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 0.7547533094882966,
654
+ "epoch": 0.52,
655
+ "grad_norm": 4.812737941741943,
656
+ "learning_rate": 9.999899215547273e-05,
657
+ "loss": 0.36,
658
+ "mean_token_accuracy": 0.8604591488838196,
659
+ "num_tokens": 652518.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 0.7455555617809295,
664
+ "epoch": 0.528,
665
+ "grad_norm": 4.497723579406738,
666
+ "learning_rate": 9.99979773188675e-05,
667
+ "loss": 0.3779,
668
+ "mean_token_accuracy": 0.8556386411190033,
669
+ "num_tokens": 662510.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 0.7497033298015594,
674
+ "epoch": 0.536,
675
+ "grad_norm": 2.8484747409820557,
676
+ "learning_rate": 9.999661254943096e-05,
677
+ "loss": 0.3728,
678
+ "mean_token_accuracy": 0.8578177571296692,
679
+ "num_tokens": 672542.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 0.7327328979969024,
684
+ "epoch": 0.544,
685
+ "grad_norm": 3.5998294353485107,
686
+ "learning_rate": 9.999489785671501e-05,
687
+ "loss": 0.3552,
688
+ "mean_token_accuracy": 0.8648241460323334,
689
+ "num_tokens": 682614.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 0.7525190949440003,
694
+ "epoch": 0.552,
695
+ "grad_norm": 3.5004866123199463,
696
+ "learning_rate": 9.99928332527207e-05,
697
+ "loss": 0.3843,
698
+ "mean_token_accuracy": 0.8582637786865235,
699
+ "num_tokens": 692618.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 0.7497900485992431,
704
+ "epoch": 0.56,
705
+ "grad_norm": 4.519836902618408,
706
+ "learning_rate": 9.999041875189808e-05,
707
+ "loss": 0.3431,
708
+ "mean_token_accuracy": 0.8670572757720947,
709
+ "num_tokens": 702633.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 0.77483931183815,
714
+ "epoch": 0.568,
715
+ "grad_norm": 3.1947054862976074,
716
+ "learning_rate": 9.998765437114606e-05,
717
+ "loss": 0.4002,
718
+ "mean_token_accuracy": 0.8486331045627594,
719
+ "num_tokens": 712707.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 0.7584193348884583,
724
+ "epoch": 0.576,
725
+ "grad_norm": 3.9025089740753174,
726
+ "learning_rate": 9.998454012981241e-05,
727
+ "loss": 0.3547,
728
+ "mean_token_accuracy": 0.8697766363620758,
729
+ "num_tokens": 722760.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 0.7460690081119538,
734
+ "epoch": 0.584,
735
+ "grad_norm": 4.149205684661865,
736
+ "learning_rate": 9.99810760496935e-05,
737
+ "loss": 0.3444,
738
+ "mean_token_accuracy": 0.8667214512825012,
739
+ "num_tokens": 732748.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 0.7551231920719147,
744
+ "epoch": 0.592,
745
+ "grad_norm": 2.7930212020874023,
746
+ "learning_rate": 9.997726215503422e-05,
747
+ "loss": 0.3648,
748
+ "mean_token_accuracy": 0.8609663844108582,
749
+ "num_tokens": 742797.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 0.7414549589157104,
754
+ "epoch": 0.6,
755
+ "grad_norm": 3.0811150074005127,
756
+ "learning_rate": 9.997309847252781e-05,
757
+ "loss": 0.3594,
758
+ "mean_token_accuracy": 0.873071813583374,
759
+ "num_tokens": 752710.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 0.7489046216011047,
764
+ "epoch": 0.608,
765
+ "grad_norm": 3.5512616634368896,
766
+ "learning_rate": 9.99685850313156e-05,
767
+ "loss": 0.3546,
768
+ "mean_token_accuracy": 0.8655755579471588,
769
+ "num_tokens": 762688.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 0.733052384853363,
774
+ "epoch": 0.616,
775
+ "grad_norm": 4.369715213775635,
776
+ "learning_rate": 9.99637218629869e-05,
777
+ "loss": 0.3417,
778
+ "mean_token_accuracy": 0.8683482468128204,
779
+ "num_tokens": 772650.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 0.7423468112945557,
784
+ "epoch": 0.624,
785
+ "grad_norm": 4.777336597442627,
786
+ "learning_rate": 9.995850900157875e-05,
787
+ "loss": 0.357,
788
+ "mean_token_accuracy": 0.8606196939945221,
789
+ "num_tokens": 782702.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 0.7481508612632751,
794
+ "epoch": 0.632,
795
+ "grad_norm": 4.678175926208496,
796
+ "learning_rate": 9.995294648357565e-05,
797
+ "loss": 0.3567,
798
+ "mean_token_accuracy": 0.865706866979599,
799
+ "num_tokens": 792664.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 0.7382378697395324,
804
+ "epoch": 0.64,
805
+ "grad_norm": 3.274829149246216,
806
+ "learning_rate": 9.99470343479093e-05,
807
+ "loss": 0.3603,
808
+ "mean_token_accuracy": 0.8626951456069947,
809
+ "num_tokens": 802737.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 0.7525390565395356,
814
+ "epoch": 0.648,
815
+ "grad_norm": 5.102212905883789,
816
+ "learning_rate": 9.994077263595842e-05,
817
+ "loss": 0.3633,
818
+ "mean_token_accuracy": 0.8564347326755524,
819
+ "num_tokens": 812785.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 0.7348288774490357,
824
+ "epoch": 0.656,
825
+ "grad_norm": 3.2849156856536865,
826
+ "learning_rate": 9.993416139154834e-05,
827
+ "loss": 0.3207,
828
+ "mean_token_accuracy": 0.8772452592849731,
829
+ "num_tokens": 822907.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 0.7165950059890747,
834
+ "epoch": 0.664,
835
+ "grad_norm": 4.360360145568848,
836
+ "learning_rate": 9.992720066095074e-05,
837
+ "loss": 0.319,
838
+ "mean_token_accuracy": 0.8817264854907989,
839
+ "num_tokens": 832978.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 0.7572665691375733,
844
+ "epoch": 0.672,
845
+ "grad_norm": 3.737704038619995,
846
+ "learning_rate": 9.99198904928834e-05,
847
+ "loss": 0.3518,
848
+ "mean_token_accuracy": 0.8672956347465515,
849
+ "num_tokens": 843010.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 0.7376816928386688,
854
+ "epoch": 0.68,
855
+ "grad_norm": 3.763667345046997,
856
+ "learning_rate": 9.99122309385097e-05,
857
+ "loss": 0.3343,
858
+ "mean_token_accuracy": 0.8720453321933747,
859
+ "num_tokens": 853158.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 0.738130909204483,
864
+ "epoch": 0.688,
865
+ "grad_norm": 3.451171636581421,
866
+ "learning_rate": 9.990422205143842e-05,
867
+ "loss": 0.3337,
868
+ "mean_token_accuracy": 0.8736945927143097,
869
+ "num_tokens": 863197.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 0.7318816602230072,
874
+ "epoch": 0.696,
875
+ "grad_norm": 4.782471656799316,
876
+ "learning_rate": 9.989586388772327e-05,
877
+ "loss": 0.3302,
878
+ "mean_token_accuracy": 0.8774139165878296,
879
+ "num_tokens": 873186.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 0.7257109045982361,
884
+ "epoch": 0.704,
885
+ "grad_norm": 4.2577714920043945,
886
+ "learning_rate": 9.988715650586255e-05,
887
+ "loss": 0.3267,
888
+ "mean_token_accuracy": 0.8722849547863006,
889
+ "num_tokens": 882902.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 0.7249192893505096,
894
+ "epoch": 0.712,
895
+ "grad_norm": 4.787215709686279,
896
+ "learning_rate": 9.987809996679868e-05,
897
+ "loss": 0.3538,
898
+ "mean_token_accuracy": 0.8667027592658997,
899
+ "num_tokens": 892970.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 0.734320092201233,
904
+ "epoch": 0.72,
905
+ "grad_norm": 4.3855061531066895,
906
+ "learning_rate": 9.986869433391786e-05,
907
+ "loss": 0.3629,
908
+ "mean_token_accuracy": 0.8576407015323639,
909
+ "num_tokens": 902925.0,
910
+ "step": 900
911
+ },
912
+ {
913
+ "entropy": 0.7197588086128235,
914
+ "epoch": 0.728,
915
+ "grad_norm": 3.845344305038452,
916
+ "learning_rate": 9.985893967304953e-05,
917
+ "loss": 0.3334,
918
+ "mean_token_accuracy": 0.8752871453762054,
919
+ "num_tokens": 913073.0,
920
+ "step": 910
921
+ },
922
+ {
923
+ "entropy": 0.7076159596443177,
924
+ "epoch": 0.736,
925
+ "grad_norm": 4.655667304992676,
926
+ "learning_rate": 9.984883605246596e-05,
927
+ "loss": 0.3553,
928
+ "mean_token_accuracy": 0.85735222697258,
929
+ "num_tokens": 923177.0,
930
+ "step": 920
931
+ },
932
+ {
933
+ "entropy": 0.6949739217758178,
934
+ "epoch": 0.744,
935
+ "grad_norm": 4.328896999359131,
936
+ "learning_rate": 9.983838354288181e-05,
937
+ "loss": 0.3114,
938
+ "mean_token_accuracy": 0.8794396817684174,
939
+ "num_tokens": 933175.0,
940
+ "step": 930
941
+ },
942
+ {
943
+ "entropy": 0.7136138260364533,
944
+ "epoch": 0.752,
945
+ "grad_norm": 3.6101481914520264,
946
+ "learning_rate": 9.982758221745355e-05,
947
+ "loss": 0.3398,
948
+ "mean_token_accuracy": 0.8673068225383759,
949
+ "num_tokens": 943216.0,
950
+ "step": 940
951
+ },
952
+ {
953
+ "entropy": 0.7149393677711486,
954
+ "epoch": 0.76,
955
+ "grad_norm": 4.676361560821533,
956
+ "learning_rate": 9.981643215177901e-05,
957
+ "loss": 0.3454,
958
+ "mean_token_accuracy": 0.8639320135116577,
959
+ "num_tokens": 953195.0,
960
+ "step": 950
961
+ },
962
+ {
963
+ "entropy": 0.7293311178684234,
964
+ "epoch": 0.768,
965
+ "grad_norm": 4.241588592529297,
966
+ "learning_rate": 9.98049334238968e-05,
967
+ "loss": 0.3267,
968
+ "mean_token_accuracy": 0.8770649194717407,
969
+ "num_tokens": 963295.0,
970
+ "step": 960
971
+ },
972
+ {
973
+ "entropy": 0.6864521920680999,
974
+ "epoch": 0.776,
975
+ "grad_norm": 4.124149322509766,
976
+ "learning_rate": 9.979308611428588e-05,
977
+ "loss": 0.3475,
978
+ "mean_token_accuracy": 0.8687545955181122,
979
+ "num_tokens": 973211.0,
980
+ "step": 970
981
+ },
982
+ {
983
+ "entropy": 0.7115203201770782,
984
+ "epoch": 0.784,
985
+ "grad_norm": 2.776160478591919,
986
+ "learning_rate": 9.978089030586482e-05,
987
+ "loss": 0.3283,
988
+ "mean_token_accuracy": 0.8781632363796235,
989
+ "num_tokens": 983423.0,
990
+ "step": 980
991
+ },
992
+ {
993
+ "entropy": 0.70510174036026,
994
+ "epoch": 0.792,
995
+ "grad_norm": 4.5464186668396,
996
+ "learning_rate": 9.976834608399135e-05,
997
+ "loss": 0.3233,
998
+ "mean_token_accuracy": 0.8736263334751129,
999
+ "num_tokens": 993383.0,
1000
+ "step": 990
1001
+ },
1002
+ {
1003
+ "entropy": 0.6919874429702759,
1004
+ "epoch": 0.8,
1005
+ "grad_norm": 3.289616346359253,
1006
+ "learning_rate": 9.975545353646172e-05,
1007
+ "loss": 0.317,
1008
+ "mean_token_accuracy": 0.8773585438728333,
1009
+ "num_tokens": 1003617.0,
1010
+ "step": 1000
1011
+ },
1012
+ {
1013
+ "entropy": 0.7038690447807312,
1014
+ "epoch": 0.808,
1015
+ "grad_norm": 3.4383840560913086,
1016
+ "learning_rate": 9.974221275351012e-05,
1017
+ "loss": 0.3038,
1018
+ "mean_token_accuracy": 0.8848366022109986,
1019
+ "num_tokens": 1013574.0,
1020
+ "step": 1010
1021
+ },
1022
+ {
1023
+ "entropy": 0.6912132382392884,
1024
+ "epoch": 0.816,
1025
+ "grad_norm": 3.7912769317626953,
1026
+ "learning_rate": 9.972862382780795e-05,
1027
+ "loss": 0.3291,
1028
+ "mean_token_accuracy": 0.8741970837116242,
1029
+ "num_tokens": 1023678.0,
1030
+ "step": 1020
1031
+ },
1032
+ {
1033
+ "entropy": 0.6911644101142883,
1034
+ "epoch": 0.824,
1035
+ "grad_norm": 3.905447006225586,
1036
+ "learning_rate": 9.971468685446332e-05,
1037
+ "loss": 0.2983,
1038
+ "mean_token_accuracy": 0.8851586222648621,
1039
+ "num_tokens": 1033772.0,
1040
+ "step": 1030
1041
+ },
1042
+ {
1043
+ "entropy": 0.7238000333309174,
1044
+ "epoch": 0.832,
1045
+ "grad_norm": 3.6505768299102783,
1046
+ "learning_rate": 9.970040193102024e-05,
1047
+ "loss": 0.322,
1048
+ "mean_token_accuracy": 0.8771763265132904,
1049
+ "num_tokens": 1043688.0,
1050
+ "step": 1040
1051
+ },
1052
+ {
1053
+ "entropy": 0.7082896769046784,
1054
+ "epoch": 0.84,
1055
+ "grad_norm": 2.9899954795837402,
1056
+ "learning_rate": 9.968576915745807e-05,
1057
+ "loss": 0.3202,
1058
+ "mean_token_accuracy": 0.8733674585819244,
1059
+ "num_tokens": 1053816.0,
1060
+ "step": 1050
1061
+ },
1062
+ {
1063
+ "entropy": 0.726912397146225,
1064
+ "epoch": 0.848,
1065
+ "grad_norm": 3.2128050327301025,
1066
+ "learning_rate": 9.967078863619065e-05,
1067
+ "loss": 0.3469,
1068
+ "mean_token_accuracy": 0.8619545817375183,
1069
+ "num_tokens": 1063713.0,
1070
+ "step": 1060
1071
+ },
1072
+ {
1073
+ "entropy": 0.7287257611751556,
1074
+ "epoch": 0.856,
1075
+ "grad_norm": 4.8999714851379395,
1076
+ "learning_rate": 9.96554604720658e-05,
1077
+ "loss": 0.3387,
1078
+ "mean_token_accuracy": 0.8722339987754821,
1079
+ "num_tokens": 1073905.0,
1080
+ "step": 1070
1081
+ },
1082
+ {
1083
+ "entropy": 0.7408074200153351,
1084
+ "epoch": 0.864,
1085
+ "grad_norm": 2.664285898208618,
1086
+ "learning_rate": 9.963978477236437e-05,
1087
+ "loss": 0.3379,
1088
+ "mean_token_accuracy": 0.8713842570781708,
1089
+ "num_tokens": 1083866.0,
1090
+ "step": 1080
1091
+ },
1092
+ {
1093
+ "entropy": 0.7120798885822296,
1094
+ "epoch": 0.872,
1095
+ "grad_norm": 4.573596954345703,
1096
+ "learning_rate": 9.962376164679968e-05,
1097
+ "loss": 0.3133,
1098
+ "mean_token_accuracy": 0.8781111538410187,
1099
+ "num_tokens": 1093886.0,
1100
+ "step": 1090
1101
+ },
1102
+ {
1103
+ "entropy": 0.6998519122600555,
1104
+ "epoch": 0.88,
1105
+ "grad_norm": 2.1679275035858154,
1106
+ "learning_rate": 9.960739120751661e-05,
1107
+ "loss": 0.3348,
1108
+ "mean_token_accuracy": 0.8770085752010346,
1109
+ "num_tokens": 1103980.0,
1110
+ "step": 1100
1111
+ },
1112
+ {
1113
+ "entropy": 0.7093372285366059,
1114
+ "epoch": 0.888,
1115
+ "grad_norm": 4.117437839508057,
1116
+ "learning_rate": 9.959067356909086e-05,
1117
+ "loss": 0.3239,
1118
+ "mean_token_accuracy": 0.8707855939865112,
1119
+ "num_tokens": 1113959.0,
1120
+ "step": 1110
1121
+ },
1122
+ {
1123
+ "entropy": 0.7140217363834381,
1124
+ "epoch": 0.896,
1125
+ "grad_norm": 3.9262735843658447,
1126
+ "learning_rate": 9.957360884852817e-05,
1127
+ "loss": 0.3105,
1128
+ "mean_token_accuracy": 0.8786974430084229,
1129
+ "num_tokens": 1123920.0,
1130
+ "step": 1120
1131
+ },
1132
+ {
1133
+ "entropy": 0.7165806293487549,
1134
+ "epoch": 0.904,
1135
+ "grad_norm": 3.4237773418426514,
1136
+ "learning_rate": 9.955619716526355e-05,
1137
+ "loss": 0.2988,
1138
+ "mean_token_accuracy": 0.8893916308879852,
1139
+ "num_tokens": 1133883.0,
1140
+ "step": 1130
1141
+ },
1142
+ {
1143
+ "entropy": 0.7115492939949035,
1144
+ "epoch": 0.912,
1145
+ "grad_norm": 5.193104267120361,
1146
+ "learning_rate": 9.953843864116024e-05,
1147
+ "loss": 0.2975,
1148
+ "mean_token_accuracy": 0.8788837730884552,
1149
+ "num_tokens": 1143953.0,
1150
+ "step": 1140
1151
+ },
1152
+ {
1153
+ "entropy": 0.738818782567978,
1154
+ "epoch": 0.92,
1155
+ "grad_norm": 4.208317279815674,
1156
+ "learning_rate": 9.952033340050914e-05,
1157
+ "loss": 0.3082,
1158
+ "mean_token_accuracy": 0.8904856204986572,
1159
+ "num_tokens": 1153991.0,
1160
+ "step": 1150
1161
+ },
1162
+ {
1163
+ "entropy": 0.7402492463588715,
1164
+ "epoch": 0.928,
1165
+ "grad_norm": 3.7344741821289062,
1166
+ "learning_rate": 9.95018815700277e-05,
1167
+ "loss": 0.2897,
1168
+ "mean_token_accuracy": 0.8875938773155212,
1169
+ "num_tokens": 1163916.0,
1170
+ "step": 1160
1171
+ },
1172
+ {
1173
+ "entropy": 0.7180757343769073,
1174
+ "epoch": 0.936,
1175
+ "grad_norm": 3.379906415939331,
1176
+ "learning_rate": 9.948308327885921e-05,
1177
+ "loss": 0.3012,
1178
+ "mean_token_accuracy": 0.882535457611084,
1179
+ "num_tokens": 1173898.0,
1180
+ "step": 1170
1181
+ },
1182
+ {
1183
+ "entropy": 0.7472505629062652,
1184
+ "epoch": 0.944,
1185
+ "grad_norm": 3.1298375129699707,
1186
+ "learning_rate": 9.946393865857175e-05,
1187
+ "loss": 0.3208,
1188
+ "mean_token_accuracy": 0.8773401141166687,
1189
+ "num_tokens": 1183791.0,
1190
+ "step": 1180
1191
+ },
1192
+ {
1193
+ "entropy": 0.705861485004425,
1194
+ "epoch": 0.952,
1195
+ "grad_norm": 4.013529300689697,
1196
+ "learning_rate": 9.944444784315737e-05,
1197
+ "loss": 0.2821,
1198
+ "mean_token_accuracy": 0.8861022651195526,
1199
+ "num_tokens": 1193813.0,
1200
+ "step": 1190
1201
+ },
1202
+ {
1203
+ "entropy": 0.699193000793457,
1204
+ "epoch": 0.96,
1205
+ "grad_norm": 5.319438457489014,
1206
+ "learning_rate": 9.942461096903111e-05,
1207
+ "loss": 0.3386,
1208
+ "mean_token_accuracy": 0.8674045443534851,
1209
+ "num_tokens": 1203738.0,
1210
+ "step": 1200
1211
+ },
1212
+ {
1213
+ "entropy": 0.7452460646629333,
1214
+ "epoch": 0.968,
1215
+ "grad_norm": 4.127198696136475,
1216
+ "learning_rate": 9.940442817503006e-05,
1217
+ "loss": 0.3312,
1218
+ "mean_token_accuracy": 0.8679324150085449,
1219
+ "num_tokens": 1213769.0,
1220
+ "step": 1210
1221
+ },
1222
+ {
1223
+ "entropy": 0.709743332862854,
1224
+ "epoch": 0.976,
1225
+ "grad_norm": 3.213073492050171,
1226
+ "learning_rate": 9.938389960241237e-05,
1227
+ "loss": 0.3247,
1228
+ "mean_token_accuracy": 0.8760505378246307,
1229
+ "num_tokens": 1223599.0,
1230
+ "step": 1220
1231
+ },
1232
+ {
1233
+ "entropy": 0.6922394454479217,
1234
+ "epoch": 0.984,
1235
+ "grad_norm": 5.325689315795898,
1236
+ "learning_rate": 9.93630253948563e-05,
1237
+ "loss": 0.3179,
1238
+ "mean_token_accuracy": 0.8699888408184051,
1239
+ "num_tokens": 1233633.0,
1240
+ "step": 1230
1241
+ },
1242
+ {
1243
+ "entropy": 0.7295576393604278,
1244
+ "epoch": 0.992,
1245
+ "grad_norm": 3.195913791656494,
1246
+ "learning_rate": 9.934180569845917e-05,
1247
+ "loss": 0.3064,
1248
+ "mean_token_accuracy": 0.8825580894947052,
1249
+ "num_tokens": 1243671.0,
1250
+ "step": 1240
1251
+ },
1252
+ {
1253
+ "entropy": 0.7127263069152832,
1254
+ "epoch": 1.0,
1255
+ "grad_norm": 3.3763585090637207,
1256
+ "learning_rate": 9.932024066173635e-05,
1257
+ "loss": 0.3251,
1258
+ "mean_token_accuracy": 0.8774601638317108,
1259
+ "num_tokens": 1253644.0,
1260
+ "step": 1250
1261
+ }
1262
+ ],
1263
+ "logging_steps": 10,
1264
+ "max_steps": 12500,
1265
+ "num_input_tokens_seen": 0,
1266
+ "num_train_epochs": 10,
1267
+ "save_steps": 500,
1268
+ "stateful_callbacks": {
1269
+ "TrainerControl": {
1270
+ "args": {
1271
+ "should_epoch_stop": false,
1272
+ "should_evaluate": false,
1273
+ "should_log": false,
1274
+ "should_save": true,
1275
+ "should_training_stop": false
1276
+ },
1277
+ "attributes": {}
1278
+ }
1279
+ },
1280
+ "total_flos": 3.097584287889408e+16,
1281
+ "train_batch_size": 8,
1282
+ "trial_name": null,
1283
+ "trial_params": null
1284
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-1250/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b25b8d8cffd67ea351659b350427764e9a6dcc4d1f692fe42a9968c21bd1cc6
3
+ size 6417
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:google/gemma-3-4b-it
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 0.19.1
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "google/gemma-3-4b-it",
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": 0.0,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 8,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "down_proj",
34
+ "gate_proj",
35
+ "o_proj",
36
+ "k_proj",
37
+ "up_proj",
38
+ "v_proj",
39
+ "q_proj"
40
+ ],
41
+ "target_parameters": null,
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bb70dcda4b42fd284f3a34794b8278f4ecb4d143e214d35a922517e5cff749e6
3
+ size 65674128
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
checkpoints/otter_gemma3_4b_r8_a32_adamw_e10_lr1e-4_s3_baseline/checkpoint-12500/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}