agu18dec commited on
Commit
e77c492
·
verified ·
1 Parent(s): d0d7f35

add checkpoint cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys

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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/README.md +61 -0
  3. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/adapter_config.json +48 -0
  4. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/adapter_model.safetensors +3 -0
  5. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/added_tokens.json +24 -0
  6. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/chat_template.jinja +54 -0
  7. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/README.md +209 -0
  8. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/adapter_config.json +48 -0
  9. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/adapter_model.safetensors +3 -0
  10. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/added_tokens.json +24 -0
  11. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/chat_template.jinja +54 -0
  12. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/merges.txt +0 -0
  13. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/special_tokens_map.json +31 -0
  14. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/tokenizer.json +3 -0
  15. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/tokenizer_config.json +207 -0
  16. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/trainer_state.json +1044 -0
  17. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/training_args.bin +3 -0
  18. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/vocab.json +0 -0
  19. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/README.md +209 -0
  20. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/adapter_config.json +48 -0
  21. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/adapter_model.safetensors +3 -0
  22. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/added_tokens.json +24 -0
  23. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/chat_template.jinja +54 -0
  24. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/merges.txt +0 -0
  25. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/special_tokens_map.json +31 -0
  26. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/tokenizer.json +3 -0
  27. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/tokenizer_config.json +207 -0
  28. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/trainer_state.json +0 -0
  29. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/training_args.bin +3 -0
  30. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/vocab.json +0 -0
  31. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/README.md +209 -0
  32. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/adapter_config.json +48 -0
  33. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/adapter_model.safetensors +3 -0
  34. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/added_tokens.json +24 -0
  35. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/chat_template.jinja +54 -0
  36. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/merges.txt +0 -0
  37. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/special_tokens_map.json +31 -0
  38. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/tokenizer.json +3 -0
  39. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/tokenizer_config.json +207 -0
  40. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/trainer_state.json +2064 -0
  41. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/training_args.bin +3 -0
  42. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/vocab.json +0 -0
  43. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/README.md +209 -0
  44. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/adapter_config.json +48 -0
  45. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/adapter_model.safetensors +3 -0
  46. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/added_tokens.json +24 -0
  47. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/chat_template.jinja +54 -0
  48. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/merges.txt +0 -0
  49. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/special_tokens_map.json +31 -0
  50. checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/tokenizer.json +3 -0
.gitattributes CHANGED
@@ -589,3 +589,14 @@ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/chec
589
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/checkpoint-8648/tokenizer.json filter=lfs diff=lfs merge=lfs -text
590
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/checkpoint-9729/tokenizer.json filter=lfs diff=lfs merge=lfs -text
591
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
589
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/checkpoint-8648/tokenizer.json filter=lfs diff=lfs merge=lfs -text
590
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/checkpoint-9729/tokenizer.json filter=lfs diff=lfs merge=lfs -text
591
  checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a4_B1_L20_noSys/tokenizer.json filter=lfs diff=lfs merge=lfs -text
592
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/tokenizer.json filter=lfs diff=lfs merge=lfs -text
593
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/tokenizer.json filter=lfs diff=lfs merge=lfs -text
594
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/tokenizer.json filter=lfs diff=lfs merge=lfs -text
595
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/tokenizer.json filter=lfs diff=lfs merge=lfs -text
596
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-4072/tokenizer.json filter=lfs diff=lfs merge=lfs -text
597
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-5090/tokenizer.json filter=lfs diff=lfs merge=lfs -text
598
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-6108/tokenizer.json filter=lfs diff=lfs merge=lfs -text
599
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-7126/tokenizer.json filter=lfs diff=lfs merge=lfs -text
600
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-8144/tokenizer.json filter=lfs diff=lfs merge=lfs -text
601
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-9162/tokenizer.json filter=lfs diff=lfs merge=lfs -text
602
+ checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/tokenizer.json filter=lfs diff=lfs merge=lfs -text
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/README.md ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
4
+ model_name: cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ licence: license
12
+ pipeline_tag: text-generation
13
+ ---
14
+
15
+ # Model Card for cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys
16
+
17
+ This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
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/lglg8c92)
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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/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": "Qwen/Qwen2.5-7B-Instruct",
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
+ "v_proj",
36
+ "o_proj",
37
+ "up_proj",
38
+ "q_proj",
39
+ "k_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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:381732958f79fd21a1d81d99b3da9598d3ece25b8d96f4eb721a0f5a6e987c38
3
+ size 80792096
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/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": "Qwen/Qwen2.5-7B-Instruct",
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
+ "v_proj",
36
+ "o_proj",
37
+ "up_proj",
38
+ "q_proj",
39
+ "k_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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:596c7bc50e314ac66495722616bce02e4951620b0536d5c59cb0ab960f5b9304
3
+ size 80792096
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
3
+ size 11421896
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 131072,
203
+ "pad_token": "<|endoftext|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/trainer_state.json ADDED
@@ -0,0 +1,1044 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": 1018,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.238373827934265,
14
+ "epoch": 0.009823182711198428,
15
+ "grad_norm": 2.1393158435821533,
16
+ "learning_rate": 1.768172888015717e-06,
17
+ "loss": 0.5677,
18
+ "mean_token_accuracy": 0.7972675561904907,
19
+ "num_tokens": 13613.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 1.248021376132965,
24
+ "epoch": 0.019646365422396856,
25
+ "grad_norm": 2.1040091514587402,
26
+ "learning_rate": 3.732809430255403e-06,
27
+ "loss": 0.6091,
28
+ "mean_token_accuracy": 0.7844378292560578,
29
+ "num_tokens": 27766.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 1.2259408831596375,
34
+ "epoch": 0.029469548133595286,
35
+ "grad_norm": 2.8529012203216553,
36
+ "learning_rate": 5.697445972495088e-06,
37
+ "loss": 0.6106,
38
+ "mean_token_accuracy": 0.7926133036613464,
39
+ "num_tokens": 41975.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 1.241147220134735,
44
+ "epoch": 0.03929273084479371,
45
+ "grad_norm": 1.9179528951644897,
46
+ "learning_rate": 7.662082514734775e-06,
47
+ "loss": 0.5673,
48
+ "mean_token_accuracy": 0.7996828734874726,
49
+ "num_tokens": 55356.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 1.2450526833534241,
54
+ "epoch": 0.04911591355599214,
55
+ "grad_norm": 2.696981191635132,
56
+ "learning_rate": 9.62671905697446e-06,
57
+ "loss": 0.5686,
58
+ "mean_token_accuracy": 0.7941810250282287,
59
+ "num_tokens": 69627.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 1.2605302929878235,
64
+ "epoch": 0.05893909626719057,
65
+ "grad_norm": 2.4317052364349365,
66
+ "learning_rate": 1.1591355599214145e-05,
67
+ "loss": 0.5802,
68
+ "mean_token_accuracy": 0.7867559194564819,
69
+ "num_tokens": 82999.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 1.2502994418144227,
74
+ "epoch": 0.068762278978389,
75
+ "grad_norm": 2.431112289428711,
76
+ "learning_rate": 1.3555992141453833e-05,
77
+ "loss": 0.5592,
78
+ "mean_token_accuracy": 0.7943781077861786,
79
+ "num_tokens": 96494.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 1.2417351365089417,
84
+ "epoch": 0.07858546168958742,
85
+ "grad_norm": 1.8804676532745361,
86
+ "learning_rate": 1.5520628683693518e-05,
87
+ "loss": 0.551,
88
+ "mean_token_accuracy": 0.7976289927959442,
89
+ "num_tokens": 110116.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 1.2354993939399719,
94
+ "epoch": 0.08840864440078586,
95
+ "grad_norm": 1.887425184249878,
96
+ "learning_rate": 1.7485265225933202e-05,
97
+ "loss": 0.4783,
98
+ "mean_token_accuracy": 0.830482566356659,
99
+ "num_tokens": 123915.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 1.2492876887321471,
104
+ "epoch": 0.09823182711198428,
105
+ "grad_norm": 1.531612515449524,
106
+ "learning_rate": 1.944990176817289e-05,
107
+ "loss": 0.5771,
108
+ "mean_token_accuracy": 0.7916022062301635,
109
+ "num_tokens": 137813.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 1.2218821048736572,
114
+ "epoch": 0.10805500982318271,
115
+ "grad_norm": 1.4735031127929688,
116
+ "learning_rate": 2.1414538310412574e-05,
117
+ "loss": 0.5318,
118
+ "mean_token_accuracy": 0.8113921225070954,
119
+ "num_tokens": 152025.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 1.2572803258895875,
124
+ "epoch": 0.11787819253438114,
125
+ "grad_norm": 1.5297958850860596,
126
+ "learning_rate": 2.3379174852652262e-05,
127
+ "loss": 0.6333,
128
+ "mean_token_accuracy": 0.7640059947967529,
129
+ "num_tokens": 165940.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 1.228113317489624,
134
+ "epoch": 0.12770137524557956,
135
+ "grad_norm": 1.594042181968689,
136
+ "learning_rate": 2.5343811394891947e-05,
137
+ "loss": 0.5409,
138
+ "mean_token_accuracy": 0.8003769814968109,
139
+ "num_tokens": 179385.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 1.202523648738861,
144
+ "epoch": 0.137524557956778,
145
+ "grad_norm": 1.2444961071014404,
146
+ "learning_rate": 2.730844793713163e-05,
147
+ "loss": 0.4893,
148
+ "mean_token_accuracy": 0.8203648805618287,
149
+ "num_tokens": 193383.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 1.2140995144844056,
154
+ "epoch": 0.14734774066797643,
155
+ "grad_norm": 1.4760793447494507,
156
+ "learning_rate": 2.9273084479371316e-05,
157
+ "loss": 0.5903,
158
+ "mean_token_accuracy": 0.7915676176548004,
159
+ "num_tokens": 206472.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 1.2337120175361633,
164
+ "epoch": 0.15717092337917485,
165
+ "grad_norm": 1.7599576711654663,
166
+ "learning_rate": 3.123772102161101e-05,
167
+ "loss": 0.5066,
168
+ "mean_token_accuracy": 0.8161738157272339,
169
+ "num_tokens": 220423.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 1.2380502581596375,
174
+ "epoch": 0.16699410609037327,
175
+ "grad_norm": 1.5037227869033813,
176
+ "learning_rate": 3.320235756385069e-05,
177
+ "loss": 0.5422,
178
+ "mean_token_accuracy": 0.8013253211975098,
179
+ "num_tokens": 235005.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 1.2622791171073913,
184
+ "epoch": 0.17681728880157171,
185
+ "grad_norm": 1.376826286315918,
186
+ "learning_rate": 3.5166994106090376e-05,
187
+ "loss": 0.581,
188
+ "mean_token_accuracy": 0.7882379591464996,
189
+ "num_tokens": 248939.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 1.2461886525154113,
194
+ "epoch": 0.18664047151277013,
195
+ "grad_norm": 1.4486498832702637,
196
+ "learning_rate": 3.713163064833006e-05,
197
+ "loss": 0.5537,
198
+ "mean_token_accuracy": 0.7965423583984375,
199
+ "num_tokens": 263177.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 1.242757785320282,
204
+ "epoch": 0.19646365422396855,
205
+ "grad_norm": 1.8996150493621826,
206
+ "learning_rate": 3.9096267190569745e-05,
207
+ "loss": 0.518,
208
+ "mean_token_accuracy": 0.8233550667762757,
209
+ "num_tokens": 276500.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 1.2447792530059814,
214
+ "epoch": 0.206286836935167,
215
+ "grad_norm": 1.6521553993225098,
216
+ "learning_rate": 4.106090373280943e-05,
217
+ "loss": 0.4893,
218
+ "mean_token_accuracy": 0.8305010080337525,
219
+ "num_tokens": 290500.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 1.2488795518875122,
224
+ "epoch": 0.21611001964636542,
225
+ "grad_norm": 1.757602572441101,
226
+ "learning_rate": 4.302554027504912e-05,
227
+ "loss": 0.4861,
228
+ "mean_token_accuracy": 0.82521493434906,
229
+ "num_tokens": 304231.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 1.2686235189437867,
234
+ "epoch": 0.22593320235756384,
235
+ "grad_norm": 1.4095959663391113,
236
+ "learning_rate": 4.4990176817288805e-05,
237
+ "loss": 0.555,
238
+ "mean_token_accuracy": 0.8019413590431214,
239
+ "num_tokens": 317976.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 1.2709406733512878,
244
+ "epoch": 0.2357563850687623,
245
+ "grad_norm": 1.935375452041626,
246
+ "learning_rate": 4.695481335952849e-05,
247
+ "loss": 0.5649,
248
+ "mean_token_accuracy": 0.8037905693054199,
249
+ "num_tokens": 331858.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 1.2544381499290467,
254
+ "epoch": 0.2455795677799607,
255
+ "grad_norm": 1.607476830482483,
256
+ "learning_rate": 4.8919449901768174e-05,
257
+ "loss": 0.5283,
258
+ "mean_token_accuracy": 0.8084118843078614,
259
+ "num_tokens": 345259.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 1.2540257692337036,
264
+ "epoch": 0.2554027504911591,
265
+ "grad_norm": 1.4414503574371338,
266
+ "learning_rate": 5.088408644400786e-05,
267
+ "loss": 0.5299,
268
+ "mean_token_accuracy": 0.8094106495380402,
269
+ "num_tokens": 360160.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 1.2452853798866272,
274
+ "epoch": 0.26522593320235754,
275
+ "grad_norm": 1.7544183731079102,
276
+ "learning_rate": 5.284872298624754e-05,
277
+ "loss": 0.494,
278
+ "mean_token_accuracy": 0.820741331577301,
279
+ "num_tokens": 373823.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 1.2502075552940368,
284
+ "epoch": 0.275049115913556,
285
+ "grad_norm": 1.8113288879394531,
286
+ "learning_rate": 5.481335952848723e-05,
287
+ "loss": 0.5062,
288
+ "mean_token_accuracy": 0.8143646121025085,
289
+ "num_tokens": 387923.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 1.2456924200057984,
294
+ "epoch": 0.28487229862475444,
295
+ "grad_norm": 1.7740198373794556,
296
+ "learning_rate": 5.677799607072691e-05,
297
+ "loss": 0.5139,
298
+ "mean_token_accuracy": 0.8153488993644714,
299
+ "num_tokens": 401453.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 1.2440819978713988,
304
+ "epoch": 0.29469548133595286,
305
+ "grad_norm": 1.0885217189788818,
306
+ "learning_rate": 5.874263261296661e-05,
307
+ "loss": 0.5045,
308
+ "mean_token_accuracy": 0.8190208375453949,
309
+ "num_tokens": 415468.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 1.2703365564346314,
314
+ "epoch": 0.3045186640471513,
315
+ "grad_norm": 1.416458249092102,
316
+ "learning_rate": 6.0707269155206295e-05,
317
+ "loss": 0.5524,
318
+ "mean_token_accuracy": 0.8009683132171631,
319
+ "num_tokens": 428767.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 1.2677528381347656,
324
+ "epoch": 0.3143418467583497,
325
+ "grad_norm": 1.9646638631820679,
326
+ "learning_rate": 6.267190569744598e-05,
327
+ "loss": 0.6255,
328
+ "mean_token_accuracy": 0.7640788197517395,
329
+ "num_tokens": 441931.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 1.2437112927436829,
334
+ "epoch": 0.3241650294695481,
335
+ "grad_norm": 1.4724621772766113,
336
+ "learning_rate": 6.463654223968566e-05,
337
+ "loss": 0.5284,
338
+ "mean_token_accuracy": 0.8117543816566467,
339
+ "num_tokens": 455302.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 1.26444011926651,
344
+ "epoch": 0.33398821218074654,
345
+ "grad_norm": 1.810052752494812,
346
+ "learning_rate": 6.660117878192535e-05,
347
+ "loss": 0.546,
348
+ "mean_token_accuracy": 0.808152836561203,
349
+ "num_tokens": 468961.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 1.2795380353927612,
354
+ "epoch": 0.343811394891945,
355
+ "grad_norm": 1.4199846982955933,
356
+ "learning_rate": 6.856581532416503e-05,
357
+ "loss": 0.5776,
358
+ "mean_token_accuracy": 0.7861001551151275,
359
+ "num_tokens": 482094.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 1.2831590175628662,
364
+ "epoch": 0.35363457760314343,
365
+ "grad_norm": 1.4240669012069702,
366
+ "learning_rate": 7.053045186640472e-05,
367
+ "loss": 0.5551,
368
+ "mean_token_accuracy": 0.7980610370635987,
369
+ "num_tokens": 495551.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 1.3066895961761475,
374
+ "epoch": 0.36345776031434185,
375
+ "grad_norm": 3.1153318881988525,
376
+ "learning_rate": 7.249508840864441e-05,
377
+ "loss": 0.6116,
378
+ "mean_token_accuracy": 0.7829572439193726,
379
+ "num_tokens": 509826.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 1.2638443112373352,
384
+ "epoch": 0.37328094302554027,
385
+ "grad_norm": 2.1263859272003174,
386
+ "learning_rate": 7.445972495088409e-05,
387
+ "loss": 0.5183,
388
+ "mean_token_accuracy": 0.8127178907394409,
389
+ "num_tokens": 523744.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 1.2958194017410278,
394
+ "epoch": 0.3831041257367387,
395
+ "grad_norm": 1.4014490842819214,
396
+ "learning_rate": 7.642436149312378e-05,
397
+ "loss": 0.6537,
398
+ "mean_token_accuracy": 0.7570026934146881,
399
+ "num_tokens": 537454.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 1.2576130390167237,
404
+ "epoch": 0.3929273084479371,
405
+ "grad_norm": 1.755161166191101,
406
+ "learning_rate": 7.838899803536346e-05,
407
+ "loss": 0.4932,
408
+ "mean_token_accuracy": 0.8207253098487854,
409
+ "num_tokens": 551546.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 1.2616795778274537,
414
+ "epoch": 0.4027504911591356,
415
+ "grad_norm": 1.5902996063232422,
416
+ "learning_rate": 8.035363457760315e-05,
417
+ "loss": 0.5245,
418
+ "mean_token_accuracy": 0.8081269204616547,
419
+ "num_tokens": 565707.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 1.2840699076652526,
424
+ "epoch": 0.412573673870334,
425
+ "grad_norm": 1.6743026971817017,
426
+ "learning_rate": 8.231827111984284e-05,
427
+ "loss": 0.5767,
428
+ "mean_token_accuracy": 0.7862762212753296,
429
+ "num_tokens": 579728.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 1.2563459753990174,
434
+ "epoch": 0.4223968565815324,
435
+ "grad_norm": 1.193405032157898,
436
+ "learning_rate": 8.428290766208252e-05,
437
+ "loss": 0.543,
438
+ "mean_token_accuracy": 0.8090866565704345,
439
+ "num_tokens": 593579.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 1.283545970916748,
444
+ "epoch": 0.43222003929273084,
445
+ "grad_norm": 1.5221855640411377,
446
+ "learning_rate": 8.62475442043222e-05,
447
+ "loss": 0.6117,
448
+ "mean_token_accuracy": 0.7837108314037323,
449
+ "num_tokens": 606791.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 1.2693499445915222,
454
+ "epoch": 0.44204322200392926,
455
+ "grad_norm": 1.6853163242340088,
456
+ "learning_rate": 8.821218074656188e-05,
457
+ "loss": 0.5621,
458
+ "mean_token_accuracy": 0.7976293742656708,
459
+ "num_tokens": 620602.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 1.2506368160247803,
464
+ "epoch": 0.4518664047151277,
465
+ "grad_norm": 1.6164072751998901,
466
+ "learning_rate": 9.017681728880158e-05,
467
+ "loss": 0.5205,
468
+ "mean_token_accuracy": 0.807697081565857,
469
+ "num_tokens": 634566.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 1.2814919590950011,
474
+ "epoch": 0.46168958742632615,
475
+ "grad_norm": 1.7173436880111694,
476
+ "learning_rate": 9.214145383104125e-05,
477
+ "loss": 0.5411,
478
+ "mean_token_accuracy": 0.8121235728263855,
479
+ "num_tokens": 648676.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 1.2675794124603272,
484
+ "epoch": 0.4715127701375246,
485
+ "grad_norm": 1.446212649345398,
486
+ "learning_rate": 9.410609037328096e-05,
487
+ "loss": 0.5563,
488
+ "mean_token_accuracy": 0.803589540719986,
489
+ "num_tokens": 662286.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 1.2913037061691284,
494
+ "epoch": 0.481335952848723,
495
+ "grad_norm": 1.630800485610962,
496
+ "learning_rate": 9.607072691552064e-05,
497
+ "loss": 0.6166,
498
+ "mean_token_accuracy": 0.7754902184009552,
499
+ "num_tokens": 675740.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 1.2715419769287108,
504
+ "epoch": 0.4911591355599214,
505
+ "grad_norm": 1.598403811454773,
506
+ "learning_rate": 9.803536345776033e-05,
507
+ "loss": 0.5614,
508
+ "mean_token_accuracy": 0.7951632618904114,
509
+ "num_tokens": 689865.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 1.285755467414856,
514
+ "epoch": 0.5009823182711198,
515
+ "grad_norm": 2.030689001083374,
516
+ "learning_rate": 0.0001,
517
+ "loss": 0.5434,
518
+ "mean_token_accuracy": 0.8062463700771332,
519
+ "num_tokens": 703743.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 1.3047456383705138,
524
+ "epoch": 0.5108055009823183,
525
+ "grad_norm": 1.8453326225280762,
526
+ "learning_rate": 9.999973618674915e-05,
527
+ "loss": 0.6121,
528
+ "mean_token_accuracy": 0.7798721611499786,
529
+ "num_tokens": 717512.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 1.282051682472229,
534
+ "epoch": 0.5206286836935167,
535
+ "grad_norm": 1.6759898662567139,
536
+ "learning_rate": 9.999894474978048e-05,
537
+ "loss": 0.5239,
538
+ "mean_token_accuracy": 0.8078398644924164,
539
+ "num_tokens": 731162.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 1.2989009261131286,
544
+ "epoch": 0.5304518664047151,
545
+ "grad_norm": 1.7401994466781616,
546
+ "learning_rate": 9.999762569744566e-05,
547
+ "loss": 0.5816,
548
+ "mean_token_accuracy": 0.7974128127098083,
549
+ "num_tokens": 745217.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 1.3011240839958191,
554
+ "epoch": 0.5402750491159135,
555
+ "grad_norm": 1.9052543640136719,
556
+ "learning_rate": 9.999577904366405e-05,
557
+ "loss": 0.555,
558
+ "mean_token_accuracy": 0.7961248874664306,
559
+ "num_tokens": 758976.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 1.3102270722389222,
564
+ "epoch": 0.550098231827112,
565
+ "grad_norm": 1.7880445718765259,
566
+ "learning_rate": 9.999340480792247e-05,
567
+ "loss": 0.6029,
568
+ "mean_token_accuracy": 0.7876855313777924,
569
+ "num_tokens": 772471.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 1.2655692934989928,
574
+ "epoch": 0.5599214145383105,
575
+ "grad_norm": 1.7137025594711304,
576
+ "learning_rate": 9.999050301527515e-05,
577
+ "loss": 0.5436,
578
+ "mean_token_accuracy": 0.800448739528656,
579
+ "num_tokens": 785857.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 1.2898759365081787,
584
+ "epoch": 0.5697445972495089,
585
+ "grad_norm": 2.03338360786438,
586
+ "learning_rate": 9.998707369634334e-05,
587
+ "loss": 0.5647,
588
+ "mean_token_accuracy": 0.7925122499465942,
589
+ "num_tokens": 799507.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 1.2878461837768556,
594
+ "epoch": 0.5795677799607073,
595
+ "grad_norm": 1.7258025407791138,
596
+ "learning_rate": 9.998311688731503e-05,
597
+ "loss": 0.5495,
598
+ "mean_token_accuracy": 0.7970447540283203,
599
+ "num_tokens": 813884.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 1.2761369585990905,
604
+ "epoch": 0.5893909626719057,
605
+ "grad_norm": 1.9462448358535767,
606
+ "learning_rate": 9.997863262994456e-05,
607
+ "loss": 0.5295,
608
+ "mean_token_accuracy": 0.8060545325279236,
609
+ "num_tokens": 827542.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 1.2756438493728637,
614
+ "epoch": 0.5992141453831041,
615
+ "grad_norm": 2.06569242477417,
616
+ "learning_rate": 9.99736209715522e-05,
617
+ "loss": 0.5747,
618
+ "mean_token_accuracy": 0.7955709218978881,
619
+ "num_tokens": 841676.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 1.2753918766975403,
624
+ "epoch": 0.6090373280943026,
625
+ "grad_norm": 1.7314369678497314,
626
+ "learning_rate": 9.996808196502362e-05,
627
+ "loss": 0.5151,
628
+ "mean_token_accuracy": 0.8180197477340698,
629
+ "num_tokens": 855269.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 1.2783099055290221,
634
+ "epoch": 0.618860510805501,
635
+ "grad_norm": 1.6164512634277344,
636
+ "learning_rate": 9.996201566880935e-05,
637
+ "loss": 0.4961,
638
+ "mean_token_accuracy": 0.8200631260871887,
639
+ "num_tokens": 868735.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 1.2850772857666015,
644
+ "epoch": 0.6286836935166994,
645
+ "grad_norm": 1.5462535619735718,
646
+ "learning_rate": 9.995542214692418e-05,
647
+ "loss": 0.5916,
648
+ "mean_token_accuracy": 0.7909732520580292,
649
+ "num_tokens": 882232.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 1.2697942018508912,
654
+ "epoch": 0.6385068762278978,
655
+ "grad_norm": 1.9398994445800781,
656
+ "learning_rate": 9.99483014689464e-05,
657
+ "loss": 0.5054,
658
+ "mean_token_accuracy": 0.8184501647949218,
659
+ "num_tokens": 895363.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 1.3003694057464599,
664
+ "epoch": 0.6483300589390962,
665
+ "grad_norm": 1.6913245916366577,
666
+ "learning_rate": 9.994065371001724e-05,
667
+ "loss": 0.5658,
668
+ "mean_token_accuracy": 0.7982197999954224,
669
+ "num_tokens": 909912.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 1.3075840830802918,
674
+ "epoch": 0.6581532416502947,
675
+ "grad_norm": 1.5393342971801758,
676
+ "learning_rate": 9.993247895083988e-05,
677
+ "loss": 0.574,
678
+ "mean_token_accuracy": 0.7920112848281861,
679
+ "num_tokens": 923818.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 1.2735092639923096,
684
+ "epoch": 0.6679764243614931,
685
+ "grad_norm": 1.6885005235671997,
686
+ "learning_rate": 9.99237772776787e-05,
687
+ "loss": 0.539,
688
+ "mean_token_accuracy": 0.7991899967193603,
689
+ "num_tokens": 937453.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 1.2649645924568176,
694
+ "epoch": 0.6777996070726916,
695
+ "grad_norm": 1.463413953781128,
696
+ "learning_rate": 9.991454878235837e-05,
697
+ "loss": 0.5361,
698
+ "mean_token_accuracy": 0.8108624756336212,
699
+ "num_tokens": 950998.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 1.2696751356124878,
704
+ "epoch": 0.68762278978389,
705
+ "grad_norm": 1.9994075298309326,
706
+ "learning_rate": 9.990479356226288e-05,
707
+ "loss": 0.5365,
708
+ "mean_token_accuracy": 0.8130120277404785,
709
+ "num_tokens": 964386.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 1.285075318813324,
714
+ "epoch": 0.6974459724950884,
715
+ "grad_norm": 1.7897218465805054,
716
+ "learning_rate": 9.989451172033447e-05,
717
+ "loss": 0.5871,
718
+ "mean_token_accuracy": 0.7820332407951355,
719
+ "num_tokens": 978060.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 1.2756176710128784,
724
+ "epoch": 0.7072691552062869,
725
+ "grad_norm": 1.7371011972427368,
726
+ "learning_rate": 9.98837033650726e-05,
727
+ "loss": 0.5597,
728
+ "mean_token_accuracy": 0.7937583506107331,
729
+ "num_tokens": 991672.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 1.2849397659301758,
734
+ "epoch": 0.7170923379174853,
735
+ "grad_norm": 1.641719937324524,
736
+ "learning_rate": 9.987236861053274e-05,
737
+ "loss": 0.5843,
738
+ "mean_token_accuracy": 0.7939905822277069,
739
+ "num_tokens": 1005457.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 1.2925720930099487,
744
+ "epoch": 0.7269155206286837,
745
+ "grad_norm": 1.8728162050247192,
746
+ "learning_rate": 9.986050757632525e-05,
747
+ "loss": 0.5755,
748
+ "mean_token_accuracy": 0.7945402979850769,
749
+ "num_tokens": 1019406.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 1.291877806186676,
754
+ "epoch": 0.7367387033398821,
755
+ "grad_norm": 1.6056290864944458,
756
+ "learning_rate": 9.984812038761405e-05,
757
+ "loss": 0.6116,
758
+ "mean_token_accuracy": 0.7776188969612121,
759
+ "num_tokens": 1032927.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 1.3065629363059998,
764
+ "epoch": 0.7465618860510805,
765
+ "grad_norm": 1.4939526319503784,
766
+ "learning_rate": 9.983520717511529e-05,
767
+ "loss": 0.6408,
768
+ "mean_token_accuracy": 0.7670970022678375,
769
+ "num_tokens": 1045833.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 1.282605803012848,
774
+ "epoch": 0.756385068762279,
775
+ "grad_norm": 1.7990894317626953,
776
+ "learning_rate": 9.982176807509607e-05,
777
+ "loss": 0.5696,
778
+ "mean_token_accuracy": 0.7870432496070862,
779
+ "num_tokens": 1059607.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 1.2711770296096803,
784
+ "epoch": 0.7662082514734774,
785
+ "grad_norm": 1.559313416481018,
786
+ "learning_rate": 9.980780322937287e-05,
787
+ "loss": 0.5315,
788
+ "mean_token_accuracy": 0.8101322710514068,
789
+ "num_tokens": 1073031.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 1.2708292603492737,
794
+ "epoch": 0.7760314341846758,
795
+ "grad_norm": 1.5710434913635254,
796
+ "learning_rate": 9.979331278531016e-05,
797
+ "loss": 0.5539,
798
+ "mean_token_accuracy": 0.8038661122322083,
799
+ "num_tokens": 1086355.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 1.3074462771415711,
804
+ "epoch": 0.7858546168958742,
805
+ "grad_norm": 1.5835829973220825,
806
+ "learning_rate": 9.977829689581877e-05,
807
+ "loss": 0.6236,
808
+ "mean_token_accuracy": 0.7792715787887573,
809
+ "num_tokens": 1100429.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 1.296637237071991,
814
+ "epoch": 0.7956777996070727,
815
+ "grad_norm": 1.571682095527649,
816
+ "learning_rate": 9.976275571935435e-05,
817
+ "loss": 0.5913,
818
+ "mean_token_accuracy": 0.7940649032592774,
819
+ "num_tokens": 1114663.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 1.294349157810211,
824
+ "epoch": 0.8055009823182712,
825
+ "grad_norm": 1.4109233617782593,
826
+ "learning_rate": 9.974668941991561e-05,
827
+ "loss": 0.6248,
828
+ "mean_token_accuracy": 0.7714365422725677,
829
+ "num_tokens": 1128403.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 1.319439172744751,
834
+ "epoch": 0.8153241650294696,
835
+ "grad_norm": 1.6622600555419922,
836
+ "learning_rate": 9.973009816704267e-05,
837
+ "loss": 0.6399,
838
+ "mean_token_accuracy": 0.774699580669403,
839
+ "num_tokens": 1142331.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 1.302856945991516,
844
+ "epoch": 0.825147347740668,
845
+ "grad_norm": 2.4136300086975098,
846
+ "learning_rate": 9.971298213581522e-05,
847
+ "loss": 0.5716,
848
+ "mean_token_accuracy": 0.7897345960140228,
849
+ "num_tokens": 1156242.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 1.287725281715393,
854
+ "epoch": 0.8349705304518664,
855
+ "grad_norm": 1.7344591617584229,
856
+ "learning_rate": 9.96953415068507e-05,
857
+ "loss": 0.5818,
858
+ "mean_token_accuracy": 0.7853143334388732,
859
+ "num_tokens": 1170390.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 1.258513343334198,
864
+ "epoch": 0.8447937131630648,
865
+ "grad_norm": 1.8267909288406372,
866
+ "learning_rate": 9.967717646630235e-05,
867
+ "loss": 0.5366,
868
+ "mean_token_accuracy": 0.8063280463218689,
869
+ "num_tokens": 1183788.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 1.2829570293426513,
874
+ "epoch": 0.8546168958742633,
875
+ "grad_norm": 1.7665373086929321,
876
+ "learning_rate": 9.965848720585734e-05,
877
+ "loss": 0.5489,
878
+ "mean_token_accuracy": 0.7993226885795593,
879
+ "num_tokens": 1197326.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 1.3128790736198426,
884
+ "epoch": 0.8644400785854617,
885
+ "grad_norm": 1.6902852058410645,
886
+ "learning_rate": 9.963927392273462e-05,
887
+ "loss": 0.6228,
888
+ "mean_token_accuracy": 0.7713834345340729,
889
+ "num_tokens": 1211392.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 1.3291242480278016,
894
+ "epoch": 0.8742632612966601,
895
+ "grad_norm": 2.342031240463257,
896
+ "learning_rate": 9.961953681968297e-05,
897
+ "loss": 0.6504,
898
+ "mean_token_accuracy": 0.7650188624858856,
899
+ "num_tokens": 1225560.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 1.3011715769767762,
904
+ "epoch": 0.8840864440078585,
905
+ "grad_norm": 2.45995831489563,
906
+ "learning_rate": 9.959927610497874e-05,
907
+ "loss": 0.617,
908
+ "mean_token_accuracy": 0.7712440609931945,
909
+ "num_tokens": 1239533.0,
910
+ "step": 900
911
+ },
912
+ {
913
+ "entropy": 1.2857048749923705,
914
+ "epoch": 0.8939096267190569,
915
+ "grad_norm": 1.9025800228118896,
916
+ "learning_rate": 9.957849199242374e-05,
917
+ "loss": 0.5763,
918
+ "mean_token_accuracy": 0.787699168920517,
919
+ "num_tokens": 1253319.0,
920
+ "step": 910
921
+ },
922
+ {
923
+ "entropy": 1.2860328674316406,
924
+ "epoch": 0.9037328094302554,
925
+ "grad_norm": 1.6897069215774536,
926
+ "learning_rate": 9.955718470134295e-05,
927
+ "loss": 0.5671,
928
+ "mean_token_accuracy": 0.8008992373943329,
929
+ "num_tokens": 1266631.0,
930
+ "step": 920
931
+ },
932
+ {
933
+ "entropy": 1.2990724086761474,
934
+ "epoch": 0.9135559921414538,
935
+ "grad_norm": 1.771283745765686,
936
+ "learning_rate": 9.953535445658218e-05,
937
+ "loss": 0.6136,
938
+ "mean_token_accuracy": 0.7856487035751343,
939
+ "num_tokens": 1280141.0,
940
+ "step": 930
941
+ },
942
+ {
943
+ "entropy": 1.2943416357040405,
944
+ "epoch": 0.9233791748526523,
945
+ "grad_norm": 2.1040866374969482,
946
+ "learning_rate": 9.951300148850576e-05,
947
+ "loss": 0.5738,
948
+ "mean_token_accuracy": 0.7893698453903198,
949
+ "num_tokens": 1294070.0,
950
+ "step": 940
951
+ },
952
+ {
953
+ "entropy": 1.3020179510116576,
954
+ "epoch": 0.9332023575638507,
955
+ "grad_norm": 1.752038836479187,
956
+ "learning_rate": 9.949012603299404e-05,
957
+ "loss": 0.5919,
958
+ "mean_token_accuracy": 0.7839440703392029,
959
+ "num_tokens": 1308196.0,
960
+ "step": 950
961
+ },
962
+ {
963
+ "entropy": 1.3016840934753418,
964
+ "epoch": 0.9430255402750491,
965
+ "grad_norm": 1.8453019857406616,
966
+ "learning_rate": 9.946672833144097e-05,
967
+ "loss": 0.5754,
968
+ "mean_token_accuracy": 0.7904948055744171,
969
+ "num_tokens": 1322261.0,
970
+ "step": 960
971
+ },
972
+ {
973
+ "entropy": 1.2948450207710267,
974
+ "epoch": 0.9528487229862476,
975
+ "grad_norm": 1.617616891860962,
976
+ "learning_rate": 9.944280863075148e-05,
977
+ "loss": 0.5965,
978
+ "mean_token_accuracy": 0.7802974283695221,
979
+ "num_tokens": 1336225.0,
980
+ "step": 970
981
+ },
982
+ {
983
+ "entropy": 1.302824819087982,
984
+ "epoch": 0.962671905697446,
985
+ "grad_norm": 1.8175745010375977,
986
+ "learning_rate": 9.941836718333894e-05,
987
+ "loss": 0.6292,
988
+ "mean_token_accuracy": 0.7750960767269135,
989
+ "num_tokens": 1349509.0,
990
+ "step": 980
991
+ },
992
+ {
993
+ "entropy": 1.2981536149978639,
994
+ "epoch": 0.9724950884086444,
995
+ "grad_norm": 1.411348581314087,
996
+ "learning_rate": 9.939340424712247e-05,
997
+ "loss": 0.5127,
998
+ "mean_token_accuracy": 0.8160092115402222,
999
+ "num_tokens": 1363443.0,
1000
+ "step": 990
1001
+ },
1002
+ {
1003
+ "entropy": 1.321254277229309,
1004
+ "epoch": 0.9823182711198428,
1005
+ "grad_norm": 1.8093916177749634,
1006
+ "learning_rate": 9.936792008552418e-05,
1007
+ "loss": 0.6142,
1008
+ "mean_token_accuracy": 0.7801197230815887,
1009
+ "num_tokens": 1377815.0,
1010
+ "step": 1000
1011
+ },
1012
+ {
1013
+ "entropy": 1.2920042157173157,
1014
+ "epoch": 0.9921414538310412,
1015
+ "grad_norm": 2.154522657394409,
1016
+ "learning_rate": 9.934191496746647e-05,
1017
+ "loss": 0.5433,
1018
+ "mean_token_accuracy": 0.7936553716659546,
1019
+ "num_tokens": 1391706.0,
1020
+ "step": 1010
1021
+ }
1022
+ ],
1023
+ "logging_steps": 10,
1024
+ "max_steps": 10180,
1025
+ "num_input_tokens_seen": 0,
1026
+ "num_train_epochs": 10,
1027
+ "save_steps": 500,
1028
+ "stateful_callbacks": {
1029
+ "TrainerControl": {
1030
+ "args": {
1031
+ "should_epoch_stop": false,
1032
+ "should_evaluate": false,
1033
+ "should_log": false,
1034
+ "should_save": true,
1035
+ "should_training_stop": false
1036
+ },
1037
+ "attributes": {}
1038
+ }
1039
+ },
1040
+ "total_flos": 5.965273778720256e+16,
1041
+ "train_batch_size": 8,
1042
+ "trial_name": null,
1043
+ "trial_params": null
1044
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca00661b4201b9c900ba613719f42e2216580f8bd1d0e3994cb00560554804cf
3
+ size 6481
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-1018/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/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": "Qwen/Qwen2.5-7B-Instruct",
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
+ "v_proj",
36
+ "o_proj",
37
+ "up_proj",
38
+ "q_proj",
39
+ "k_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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:381732958f79fd21a1d81d99b3da9598d3ece25b8d96f4eb721a0f5a6e987c38
3
+ size 80792096
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
3
+ size 11421896
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 131072,
203
+ "pad_token": "<|endoftext|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca00661b4201b9c900ba613719f42e2216580f8bd1d0e3994cb00560554804cf
3
+ size 6481
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-10180/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/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": "Qwen/Qwen2.5-7B-Instruct",
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
+ "v_proj",
36
+ "o_proj",
37
+ "up_proj",
38
+ "q_proj",
39
+ "k_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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d05c922a29d65fbe2a55b88b10319dc70719fde2d23e3c9840293fed6f1ab313
3
+ size 80792096
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
3
+ size 11421896
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 131072,
203
+ "pad_token": "<|endoftext|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/trainer_state.json ADDED
@@ -0,0 +1,2064 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.0,
6
+ "eval_steps": 500,
7
+ "global_step": 2036,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.238373827934265,
14
+ "epoch": 0.009823182711198428,
15
+ "grad_norm": 2.1393158435821533,
16
+ "learning_rate": 1.768172888015717e-06,
17
+ "loss": 0.5677,
18
+ "mean_token_accuracy": 0.7972675561904907,
19
+ "num_tokens": 13613.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 1.248021376132965,
24
+ "epoch": 0.019646365422396856,
25
+ "grad_norm": 2.1040091514587402,
26
+ "learning_rate": 3.732809430255403e-06,
27
+ "loss": 0.6091,
28
+ "mean_token_accuracy": 0.7844378292560578,
29
+ "num_tokens": 27766.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 1.2259408831596375,
34
+ "epoch": 0.029469548133595286,
35
+ "grad_norm": 2.8529012203216553,
36
+ "learning_rate": 5.697445972495088e-06,
37
+ "loss": 0.6106,
38
+ "mean_token_accuracy": 0.7926133036613464,
39
+ "num_tokens": 41975.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 1.241147220134735,
44
+ "epoch": 0.03929273084479371,
45
+ "grad_norm": 1.9179528951644897,
46
+ "learning_rate": 7.662082514734775e-06,
47
+ "loss": 0.5673,
48
+ "mean_token_accuracy": 0.7996828734874726,
49
+ "num_tokens": 55356.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 1.2450526833534241,
54
+ "epoch": 0.04911591355599214,
55
+ "grad_norm": 2.696981191635132,
56
+ "learning_rate": 9.62671905697446e-06,
57
+ "loss": 0.5686,
58
+ "mean_token_accuracy": 0.7941810250282287,
59
+ "num_tokens": 69627.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 1.2605302929878235,
64
+ "epoch": 0.05893909626719057,
65
+ "grad_norm": 2.4317052364349365,
66
+ "learning_rate": 1.1591355599214145e-05,
67
+ "loss": 0.5802,
68
+ "mean_token_accuracy": 0.7867559194564819,
69
+ "num_tokens": 82999.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 1.2502994418144227,
74
+ "epoch": 0.068762278978389,
75
+ "grad_norm": 2.431112289428711,
76
+ "learning_rate": 1.3555992141453833e-05,
77
+ "loss": 0.5592,
78
+ "mean_token_accuracy": 0.7943781077861786,
79
+ "num_tokens": 96494.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 1.2417351365089417,
84
+ "epoch": 0.07858546168958742,
85
+ "grad_norm": 1.8804676532745361,
86
+ "learning_rate": 1.5520628683693518e-05,
87
+ "loss": 0.551,
88
+ "mean_token_accuracy": 0.7976289927959442,
89
+ "num_tokens": 110116.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 1.2354993939399719,
94
+ "epoch": 0.08840864440078586,
95
+ "grad_norm": 1.887425184249878,
96
+ "learning_rate": 1.7485265225933202e-05,
97
+ "loss": 0.4783,
98
+ "mean_token_accuracy": 0.830482566356659,
99
+ "num_tokens": 123915.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 1.2492876887321471,
104
+ "epoch": 0.09823182711198428,
105
+ "grad_norm": 1.531612515449524,
106
+ "learning_rate": 1.944990176817289e-05,
107
+ "loss": 0.5771,
108
+ "mean_token_accuracy": 0.7916022062301635,
109
+ "num_tokens": 137813.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 1.2218821048736572,
114
+ "epoch": 0.10805500982318271,
115
+ "grad_norm": 1.4735031127929688,
116
+ "learning_rate": 2.1414538310412574e-05,
117
+ "loss": 0.5318,
118
+ "mean_token_accuracy": 0.8113921225070954,
119
+ "num_tokens": 152025.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 1.2572803258895875,
124
+ "epoch": 0.11787819253438114,
125
+ "grad_norm": 1.5297958850860596,
126
+ "learning_rate": 2.3379174852652262e-05,
127
+ "loss": 0.6333,
128
+ "mean_token_accuracy": 0.7640059947967529,
129
+ "num_tokens": 165940.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 1.228113317489624,
134
+ "epoch": 0.12770137524557956,
135
+ "grad_norm": 1.594042181968689,
136
+ "learning_rate": 2.5343811394891947e-05,
137
+ "loss": 0.5409,
138
+ "mean_token_accuracy": 0.8003769814968109,
139
+ "num_tokens": 179385.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 1.202523648738861,
144
+ "epoch": 0.137524557956778,
145
+ "grad_norm": 1.2444961071014404,
146
+ "learning_rate": 2.730844793713163e-05,
147
+ "loss": 0.4893,
148
+ "mean_token_accuracy": 0.8203648805618287,
149
+ "num_tokens": 193383.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 1.2140995144844056,
154
+ "epoch": 0.14734774066797643,
155
+ "grad_norm": 1.4760793447494507,
156
+ "learning_rate": 2.9273084479371316e-05,
157
+ "loss": 0.5903,
158
+ "mean_token_accuracy": 0.7915676176548004,
159
+ "num_tokens": 206472.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 1.2337120175361633,
164
+ "epoch": 0.15717092337917485,
165
+ "grad_norm": 1.7599576711654663,
166
+ "learning_rate": 3.123772102161101e-05,
167
+ "loss": 0.5066,
168
+ "mean_token_accuracy": 0.8161738157272339,
169
+ "num_tokens": 220423.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 1.2380502581596375,
174
+ "epoch": 0.16699410609037327,
175
+ "grad_norm": 1.5037227869033813,
176
+ "learning_rate": 3.320235756385069e-05,
177
+ "loss": 0.5422,
178
+ "mean_token_accuracy": 0.8013253211975098,
179
+ "num_tokens": 235005.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 1.2622791171073913,
184
+ "epoch": 0.17681728880157171,
185
+ "grad_norm": 1.376826286315918,
186
+ "learning_rate": 3.5166994106090376e-05,
187
+ "loss": 0.581,
188
+ "mean_token_accuracy": 0.7882379591464996,
189
+ "num_tokens": 248939.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 1.2461886525154113,
194
+ "epoch": 0.18664047151277013,
195
+ "grad_norm": 1.4486498832702637,
196
+ "learning_rate": 3.713163064833006e-05,
197
+ "loss": 0.5537,
198
+ "mean_token_accuracy": 0.7965423583984375,
199
+ "num_tokens": 263177.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 1.242757785320282,
204
+ "epoch": 0.19646365422396855,
205
+ "grad_norm": 1.8996150493621826,
206
+ "learning_rate": 3.9096267190569745e-05,
207
+ "loss": 0.518,
208
+ "mean_token_accuracy": 0.8233550667762757,
209
+ "num_tokens": 276500.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 1.2447792530059814,
214
+ "epoch": 0.206286836935167,
215
+ "grad_norm": 1.6521553993225098,
216
+ "learning_rate": 4.106090373280943e-05,
217
+ "loss": 0.4893,
218
+ "mean_token_accuracy": 0.8305010080337525,
219
+ "num_tokens": 290500.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 1.2488795518875122,
224
+ "epoch": 0.21611001964636542,
225
+ "grad_norm": 1.757602572441101,
226
+ "learning_rate": 4.302554027504912e-05,
227
+ "loss": 0.4861,
228
+ "mean_token_accuracy": 0.82521493434906,
229
+ "num_tokens": 304231.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 1.2686235189437867,
234
+ "epoch": 0.22593320235756384,
235
+ "grad_norm": 1.4095959663391113,
236
+ "learning_rate": 4.4990176817288805e-05,
237
+ "loss": 0.555,
238
+ "mean_token_accuracy": 0.8019413590431214,
239
+ "num_tokens": 317976.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 1.2709406733512878,
244
+ "epoch": 0.2357563850687623,
245
+ "grad_norm": 1.935375452041626,
246
+ "learning_rate": 4.695481335952849e-05,
247
+ "loss": 0.5649,
248
+ "mean_token_accuracy": 0.8037905693054199,
249
+ "num_tokens": 331858.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 1.2544381499290467,
254
+ "epoch": 0.2455795677799607,
255
+ "grad_norm": 1.607476830482483,
256
+ "learning_rate": 4.8919449901768174e-05,
257
+ "loss": 0.5283,
258
+ "mean_token_accuracy": 0.8084118843078614,
259
+ "num_tokens": 345259.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 1.2540257692337036,
264
+ "epoch": 0.2554027504911591,
265
+ "grad_norm": 1.4414503574371338,
266
+ "learning_rate": 5.088408644400786e-05,
267
+ "loss": 0.5299,
268
+ "mean_token_accuracy": 0.8094106495380402,
269
+ "num_tokens": 360160.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 1.2452853798866272,
274
+ "epoch": 0.26522593320235754,
275
+ "grad_norm": 1.7544183731079102,
276
+ "learning_rate": 5.284872298624754e-05,
277
+ "loss": 0.494,
278
+ "mean_token_accuracy": 0.820741331577301,
279
+ "num_tokens": 373823.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 1.2502075552940368,
284
+ "epoch": 0.275049115913556,
285
+ "grad_norm": 1.8113288879394531,
286
+ "learning_rate": 5.481335952848723e-05,
287
+ "loss": 0.5062,
288
+ "mean_token_accuracy": 0.8143646121025085,
289
+ "num_tokens": 387923.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 1.2456924200057984,
294
+ "epoch": 0.28487229862475444,
295
+ "grad_norm": 1.7740198373794556,
296
+ "learning_rate": 5.677799607072691e-05,
297
+ "loss": 0.5139,
298
+ "mean_token_accuracy": 0.8153488993644714,
299
+ "num_tokens": 401453.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 1.2440819978713988,
304
+ "epoch": 0.29469548133595286,
305
+ "grad_norm": 1.0885217189788818,
306
+ "learning_rate": 5.874263261296661e-05,
307
+ "loss": 0.5045,
308
+ "mean_token_accuracy": 0.8190208375453949,
309
+ "num_tokens": 415468.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 1.2703365564346314,
314
+ "epoch": 0.3045186640471513,
315
+ "grad_norm": 1.416458249092102,
316
+ "learning_rate": 6.0707269155206295e-05,
317
+ "loss": 0.5524,
318
+ "mean_token_accuracy": 0.8009683132171631,
319
+ "num_tokens": 428767.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 1.2677528381347656,
324
+ "epoch": 0.3143418467583497,
325
+ "grad_norm": 1.9646638631820679,
326
+ "learning_rate": 6.267190569744598e-05,
327
+ "loss": 0.6255,
328
+ "mean_token_accuracy": 0.7640788197517395,
329
+ "num_tokens": 441931.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 1.2437112927436829,
334
+ "epoch": 0.3241650294695481,
335
+ "grad_norm": 1.4724621772766113,
336
+ "learning_rate": 6.463654223968566e-05,
337
+ "loss": 0.5284,
338
+ "mean_token_accuracy": 0.8117543816566467,
339
+ "num_tokens": 455302.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 1.26444011926651,
344
+ "epoch": 0.33398821218074654,
345
+ "grad_norm": 1.810052752494812,
346
+ "learning_rate": 6.660117878192535e-05,
347
+ "loss": 0.546,
348
+ "mean_token_accuracy": 0.808152836561203,
349
+ "num_tokens": 468961.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 1.2795380353927612,
354
+ "epoch": 0.343811394891945,
355
+ "grad_norm": 1.4199846982955933,
356
+ "learning_rate": 6.856581532416503e-05,
357
+ "loss": 0.5776,
358
+ "mean_token_accuracy": 0.7861001551151275,
359
+ "num_tokens": 482094.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 1.2831590175628662,
364
+ "epoch": 0.35363457760314343,
365
+ "grad_norm": 1.4240669012069702,
366
+ "learning_rate": 7.053045186640472e-05,
367
+ "loss": 0.5551,
368
+ "mean_token_accuracy": 0.7980610370635987,
369
+ "num_tokens": 495551.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 1.3066895961761475,
374
+ "epoch": 0.36345776031434185,
375
+ "grad_norm": 3.1153318881988525,
376
+ "learning_rate": 7.249508840864441e-05,
377
+ "loss": 0.6116,
378
+ "mean_token_accuracy": 0.7829572439193726,
379
+ "num_tokens": 509826.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 1.2638443112373352,
384
+ "epoch": 0.37328094302554027,
385
+ "grad_norm": 2.1263859272003174,
386
+ "learning_rate": 7.445972495088409e-05,
387
+ "loss": 0.5183,
388
+ "mean_token_accuracy": 0.8127178907394409,
389
+ "num_tokens": 523744.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 1.2958194017410278,
394
+ "epoch": 0.3831041257367387,
395
+ "grad_norm": 1.4014490842819214,
396
+ "learning_rate": 7.642436149312378e-05,
397
+ "loss": 0.6537,
398
+ "mean_token_accuracy": 0.7570026934146881,
399
+ "num_tokens": 537454.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 1.2576130390167237,
404
+ "epoch": 0.3929273084479371,
405
+ "grad_norm": 1.755161166191101,
406
+ "learning_rate": 7.838899803536346e-05,
407
+ "loss": 0.4932,
408
+ "mean_token_accuracy": 0.8207253098487854,
409
+ "num_tokens": 551546.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 1.2616795778274537,
414
+ "epoch": 0.4027504911591356,
415
+ "grad_norm": 1.5902996063232422,
416
+ "learning_rate": 8.035363457760315e-05,
417
+ "loss": 0.5245,
418
+ "mean_token_accuracy": 0.8081269204616547,
419
+ "num_tokens": 565707.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 1.2840699076652526,
424
+ "epoch": 0.412573673870334,
425
+ "grad_norm": 1.6743026971817017,
426
+ "learning_rate": 8.231827111984284e-05,
427
+ "loss": 0.5767,
428
+ "mean_token_accuracy": 0.7862762212753296,
429
+ "num_tokens": 579728.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 1.2563459753990174,
434
+ "epoch": 0.4223968565815324,
435
+ "grad_norm": 1.193405032157898,
436
+ "learning_rate": 8.428290766208252e-05,
437
+ "loss": 0.543,
438
+ "mean_token_accuracy": 0.8090866565704345,
439
+ "num_tokens": 593579.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 1.283545970916748,
444
+ "epoch": 0.43222003929273084,
445
+ "grad_norm": 1.5221855640411377,
446
+ "learning_rate": 8.62475442043222e-05,
447
+ "loss": 0.6117,
448
+ "mean_token_accuracy": 0.7837108314037323,
449
+ "num_tokens": 606791.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 1.2693499445915222,
454
+ "epoch": 0.44204322200392926,
455
+ "grad_norm": 1.6853163242340088,
456
+ "learning_rate": 8.821218074656188e-05,
457
+ "loss": 0.5621,
458
+ "mean_token_accuracy": 0.7976293742656708,
459
+ "num_tokens": 620602.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 1.2506368160247803,
464
+ "epoch": 0.4518664047151277,
465
+ "grad_norm": 1.6164072751998901,
466
+ "learning_rate": 9.017681728880158e-05,
467
+ "loss": 0.5205,
468
+ "mean_token_accuracy": 0.807697081565857,
469
+ "num_tokens": 634566.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 1.2814919590950011,
474
+ "epoch": 0.46168958742632615,
475
+ "grad_norm": 1.7173436880111694,
476
+ "learning_rate": 9.214145383104125e-05,
477
+ "loss": 0.5411,
478
+ "mean_token_accuracy": 0.8121235728263855,
479
+ "num_tokens": 648676.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 1.2675794124603272,
484
+ "epoch": 0.4715127701375246,
485
+ "grad_norm": 1.446212649345398,
486
+ "learning_rate": 9.410609037328096e-05,
487
+ "loss": 0.5563,
488
+ "mean_token_accuracy": 0.803589540719986,
489
+ "num_tokens": 662286.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 1.2913037061691284,
494
+ "epoch": 0.481335952848723,
495
+ "grad_norm": 1.630800485610962,
496
+ "learning_rate": 9.607072691552064e-05,
497
+ "loss": 0.6166,
498
+ "mean_token_accuracy": 0.7754902184009552,
499
+ "num_tokens": 675740.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 1.2715419769287108,
504
+ "epoch": 0.4911591355599214,
505
+ "grad_norm": 1.598403811454773,
506
+ "learning_rate": 9.803536345776033e-05,
507
+ "loss": 0.5614,
508
+ "mean_token_accuracy": 0.7951632618904114,
509
+ "num_tokens": 689865.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 1.285755467414856,
514
+ "epoch": 0.5009823182711198,
515
+ "grad_norm": 2.030689001083374,
516
+ "learning_rate": 0.0001,
517
+ "loss": 0.5434,
518
+ "mean_token_accuracy": 0.8062463700771332,
519
+ "num_tokens": 703743.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 1.3047456383705138,
524
+ "epoch": 0.5108055009823183,
525
+ "grad_norm": 1.8453326225280762,
526
+ "learning_rate": 9.999973618674915e-05,
527
+ "loss": 0.6121,
528
+ "mean_token_accuracy": 0.7798721611499786,
529
+ "num_tokens": 717512.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 1.282051682472229,
534
+ "epoch": 0.5206286836935167,
535
+ "grad_norm": 1.6759898662567139,
536
+ "learning_rate": 9.999894474978048e-05,
537
+ "loss": 0.5239,
538
+ "mean_token_accuracy": 0.8078398644924164,
539
+ "num_tokens": 731162.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 1.2989009261131286,
544
+ "epoch": 0.5304518664047151,
545
+ "grad_norm": 1.7401994466781616,
546
+ "learning_rate": 9.999762569744566e-05,
547
+ "loss": 0.5816,
548
+ "mean_token_accuracy": 0.7974128127098083,
549
+ "num_tokens": 745217.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 1.3011240839958191,
554
+ "epoch": 0.5402750491159135,
555
+ "grad_norm": 1.9052543640136719,
556
+ "learning_rate": 9.999577904366405e-05,
557
+ "loss": 0.555,
558
+ "mean_token_accuracy": 0.7961248874664306,
559
+ "num_tokens": 758976.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 1.3102270722389222,
564
+ "epoch": 0.550098231827112,
565
+ "grad_norm": 1.7880445718765259,
566
+ "learning_rate": 9.999340480792247e-05,
567
+ "loss": 0.6029,
568
+ "mean_token_accuracy": 0.7876855313777924,
569
+ "num_tokens": 772471.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 1.2655692934989928,
574
+ "epoch": 0.5599214145383105,
575
+ "grad_norm": 1.7137025594711304,
576
+ "learning_rate": 9.999050301527515e-05,
577
+ "loss": 0.5436,
578
+ "mean_token_accuracy": 0.800448739528656,
579
+ "num_tokens": 785857.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 1.2898759365081787,
584
+ "epoch": 0.5697445972495089,
585
+ "grad_norm": 2.03338360786438,
586
+ "learning_rate": 9.998707369634334e-05,
587
+ "loss": 0.5647,
588
+ "mean_token_accuracy": 0.7925122499465942,
589
+ "num_tokens": 799507.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 1.2878461837768556,
594
+ "epoch": 0.5795677799607073,
595
+ "grad_norm": 1.7258025407791138,
596
+ "learning_rate": 9.998311688731503e-05,
597
+ "loss": 0.5495,
598
+ "mean_token_accuracy": 0.7970447540283203,
599
+ "num_tokens": 813884.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 1.2761369585990905,
604
+ "epoch": 0.5893909626719057,
605
+ "grad_norm": 1.9462448358535767,
606
+ "learning_rate": 9.997863262994456e-05,
607
+ "loss": 0.5295,
608
+ "mean_token_accuracy": 0.8060545325279236,
609
+ "num_tokens": 827542.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 1.2756438493728637,
614
+ "epoch": 0.5992141453831041,
615
+ "grad_norm": 2.06569242477417,
616
+ "learning_rate": 9.99736209715522e-05,
617
+ "loss": 0.5747,
618
+ "mean_token_accuracy": 0.7955709218978881,
619
+ "num_tokens": 841676.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 1.2753918766975403,
624
+ "epoch": 0.6090373280943026,
625
+ "grad_norm": 1.7314369678497314,
626
+ "learning_rate": 9.996808196502362e-05,
627
+ "loss": 0.5151,
628
+ "mean_token_accuracy": 0.8180197477340698,
629
+ "num_tokens": 855269.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 1.2783099055290221,
634
+ "epoch": 0.618860510805501,
635
+ "grad_norm": 1.6164512634277344,
636
+ "learning_rate": 9.996201566880935e-05,
637
+ "loss": 0.4961,
638
+ "mean_token_accuracy": 0.8200631260871887,
639
+ "num_tokens": 868735.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 1.2850772857666015,
644
+ "epoch": 0.6286836935166994,
645
+ "grad_norm": 1.5462535619735718,
646
+ "learning_rate": 9.995542214692418e-05,
647
+ "loss": 0.5916,
648
+ "mean_token_accuracy": 0.7909732520580292,
649
+ "num_tokens": 882232.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 1.2697942018508912,
654
+ "epoch": 0.6385068762278978,
655
+ "grad_norm": 1.9398994445800781,
656
+ "learning_rate": 9.99483014689464e-05,
657
+ "loss": 0.5054,
658
+ "mean_token_accuracy": 0.8184501647949218,
659
+ "num_tokens": 895363.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 1.3003694057464599,
664
+ "epoch": 0.6483300589390962,
665
+ "grad_norm": 1.6913245916366577,
666
+ "learning_rate": 9.994065371001724e-05,
667
+ "loss": 0.5658,
668
+ "mean_token_accuracy": 0.7982197999954224,
669
+ "num_tokens": 909912.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 1.3075840830802918,
674
+ "epoch": 0.6581532416502947,
675
+ "grad_norm": 1.5393342971801758,
676
+ "learning_rate": 9.993247895083988e-05,
677
+ "loss": 0.574,
678
+ "mean_token_accuracy": 0.7920112848281861,
679
+ "num_tokens": 923818.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 1.2735092639923096,
684
+ "epoch": 0.6679764243614931,
685
+ "grad_norm": 1.6885005235671997,
686
+ "learning_rate": 9.99237772776787e-05,
687
+ "loss": 0.539,
688
+ "mean_token_accuracy": 0.7991899967193603,
689
+ "num_tokens": 937453.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 1.2649645924568176,
694
+ "epoch": 0.6777996070726916,
695
+ "grad_norm": 1.463413953781128,
696
+ "learning_rate": 9.991454878235837e-05,
697
+ "loss": 0.5361,
698
+ "mean_token_accuracy": 0.8108624756336212,
699
+ "num_tokens": 950998.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 1.2696751356124878,
704
+ "epoch": 0.68762278978389,
705
+ "grad_norm": 1.9994075298309326,
706
+ "learning_rate": 9.990479356226288e-05,
707
+ "loss": 0.5365,
708
+ "mean_token_accuracy": 0.8130120277404785,
709
+ "num_tokens": 964386.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 1.285075318813324,
714
+ "epoch": 0.6974459724950884,
715
+ "grad_norm": 1.7897218465805054,
716
+ "learning_rate": 9.989451172033447e-05,
717
+ "loss": 0.5871,
718
+ "mean_token_accuracy": 0.7820332407951355,
719
+ "num_tokens": 978060.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 1.2756176710128784,
724
+ "epoch": 0.7072691552062869,
725
+ "grad_norm": 1.7371011972427368,
726
+ "learning_rate": 9.98837033650726e-05,
727
+ "loss": 0.5597,
728
+ "mean_token_accuracy": 0.7937583506107331,
729
+ "num_tokens": 991672.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 1.2849397659301758,
734
+ "epoch": 0.7170923379174853,
735
+ "grad_norm": 1.641719937324524,
736
+ "learning_rate": 9.987236861053274e-05,
737
+ "loss": 0.5843,
738
+ "mean_token_accuracy": 0.7939905822277069,
739
+ "num_tokens": 1005457.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 1.2925720930099487,
744
+ "epoch": 0.7269155206286837,
745
+ "grad_norm": 1.8728162050247192,
746
+ "learning_rate": 9.986050757632525e-05,
747
+ "loss": 0.5755,
748
+ "mean_token_accuracy": 0.7945402979850769,
749
+ "num_tokens": 1019406.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 1.291877806186676,
754
+ "epoch": 0.7367387033398821,
755
+ "grad_norm": 1.6056290864944458,
756
+ "learning_rate": 9.984812038761405e-05,
757
+ "loss": 0.6116,
758
+ "mean_token_accuracy": 0.7776188969612121,
759
+ "num_tokens": 1032927.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 1.3065629363059998,
764
+ "epoch": 0.7465618860510805,
765
+ "grad_norm": 1.4939526319503784,
766
+ "learning_rate": 9.983520717511529e-05,
767
+ "loss": 0.6408,
768
+ "mean_token_accuracy": 0.7670970022678375,
769
+ "num_tokens": 1045833.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 1.282605803012848,
774
+ "epoch": 0.756385068762279,
775
+ "grad_norm": 1.7990894317626953,
776
+ "learning_rate": 9.982176807509607e-05,
777
+ "loss": 0.5696,
778
+ "mean_token_accuracy": 0.7870432496070862,
779
+ "num_tokens": 1059607.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 1.2711770296096803,
784
+ "epoch": 0.7662082514734774,
785
+ "grad_norm": 1.559313416481018,
786
+ "learning_rate": 9.980780322937287e-05,
787
+ "loss": 0.5315,
788
+ "mean_token_accuracy": 0.8101322710514068,
789
+ "num_tokens": 1073031.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 1.2708292603492737,
794
+ "epoch": 0.7760314341846758,
795
+ "grad_norm": 1.5710434913635254,
796
+ "learning_rate": 9.979331278531016e-05,
797
+ "loss": 0.5539,
798
+ "mean_token_accuracy": 0.8038661122322083,
799
+ "num_tokens": 1086355.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 1.3074462771415711,
804
+ "epoch": 0.7858546168958742,
805
+ "grad_norm": 1.5835829973220825,
806
+ "learning_rate": 9.977829689581877e-05,
807
+ "loss": 0.6236,
808
+ "mean_token_accuracy": 0.7792715787887573,
809
+ "num_tokens": 1100429.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 1.296637237071991,
814
+ "epoch": 0.7956777996070727,
815
+ "grad_norm": 1.571682095527649,
816
+ "learning_rate": 9.976275571935435e-05,
817
+ "loss": 0.5913,
818
+ "mean_token_accuracy": 0.7940649032592774,
819
+ "num_tokens": 1114663.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 1.294349157810211,
824
+ "epoch": 0.8055009823182712,
825
+ "grad_norm": 1.4109233617782593,
826
+ "learning_rate": 9.974668941991561e-05,
827
+ "loss": 0.6248,
828
+ "mean_token_accuracy": 0.7714365422725677,
829
+ "num_tokens": 1128403.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 1.319439172744751,
834
+ "epoch": 0.8153241650294696,
835
+ "grad_norm": 1.6622600555419922,
836
+ "learning_rate": 9.973009816704267e-05,
837
+ "loss": 0.6399,
838
+ "mean_token_accuracy": 0.774699580669403,
839
+ "num_tokens": 1142331.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 1.302856945991516,
844
+ "epoch": 0.825147347740668,
845
+ "grad_norm": 2.4136300086975098,
846
+ "learning_rate": 9.971298213581522e-05,
847
+ "loss": 0.5716,
848
+ "mean_token_accuracy": 0.7897345960140228,
849
+ "num_tokens": 1156242.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 1.287725281715393,
854
+ "epoch": 0.8349705304518664,
855
+ "grad_norm": 1.7344591617584229,
856
+ "learning_rate": 9.96953415068507e-05,
857
+ "loss": 0.5818,
858
+ "mean_token_accuracy": 0.7853143334388732,
859
+ "num_tokens": 1170390.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 1.258513343334198,
864
+ "epoch": 0.8447937131630648,
865
+ "grad_norm": 1.8267909288406372,
866
+ "learning_rate": 9.967717646630235e-05,
867
+ "loss": 0.5366,
868
+ "mean_token_accuracy": 0.8063280463218689,
869
+ "num_tokens": 1183788.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 1.2829570293426513,
874
+ "epoch": 0.8546168958742633,
875
+ "grad_norm": 1.7665373086929321,
876
+ "learning_rate": 9.965848720585734e-05,
877
+ "loss": 0.5489,
878
+ "mean_token_accuracy": 0.7993226885795593,
879
+ "num_tokens": 1197326.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 1.3128790736198426,
884
+ "epoch": 0.8644400785854617,
885
+ "grad_norm": 1.6902852058410645,
886
+ "learning_rate": 9.963927392273462e-05,
887
+ "loss": 0.6228,
888
+ "mean_token_accuracy": 0.7713834345340729,
889
+ "num_tokens": 1211392.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 1.3291242480278016,
894
+ "epoch": 0.8742632612966601,
895
+ "grad_norm": 2.342031240463257,
896
+ "learning_rate": 9.961953681968297e-05,
897
+ "loss": 0.6504,
898
+ "mean_token_accuracy": 0.7650188624858856,
899
+ "num_tokens": 1225560.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 1.3011715769767762,
904
+ "epoch": 0.8840864440078585,
905
+ "grad_norm": 2.45995831489563,
906
+ "learning_rate": 9.959927610497874e-05,
907
+ "loss": 0.617,
908
+ "mean_token_accuracy": 0.7712440609931945,
909
+ "num_tokens": 1239533.0,
910
+ "step": 900
911
+ },
912
+ {
913
+ "entropy": 1.2857048749923705,
914
+ "epoch": 0.8939096267190569,
915
+ "grad_norm": 1.9025800228118896,
916
+ "learning_rate": 9.957849199242374e-05,
917
+ "loss": 0.5763,
918
+ "mean_token_accuracy": 0.787699168920517,
919
+ "num_tokens": 1253319.0,
920
+ "step": 910
921
+ },
922
+ {
923
+ "entropy": 1.2860328674316406,
924
+ "epoch": 0.9037328094302554,
925
+ "grad_norm": 1.6897069215774536,
926
+ "learning_rate": 9.955718470134295e-05,
927
+ "loss": 0.5671,
928
+ "mean_token_accuracy": 0.8008992373943329,
929
+ "num_tokens": 1266631.0,
930
+ "step": 920
931
+ },
932
+ {
933
+ "entropy": 1.2990724086761474,
934
+ "epoch": 0.9135559921414538,
935
+ "grad_norm": 1.771283745765686,
936
+ "learning_rate": 9.953535445658218e-05,
937
+ "loss": 0.6136,
938
+ "mean_token_accuracy": 0.7856487035751343,
939
+ "num_tokens": 1280141.0,
940
+ "step": 930
941
+ },
942
+ {
943
+ "entropy": 1.2943416357040405,
944
+ "epoch": 0.9233791748526523,
945
+ "grad_norm": 2.1040866374969482,
946
+ "learning_rate": 9.951300148850576e-05,
947
+ "loss": 0.5738,
948
+ "mean_token_accuracy": 0.7893698453903198,
949
+ "num_tokens": 1294070.0,
950
+ "step": 940
951
+ },
952
+ {
953
+ "entropy": 1.3020179510116576,
954
+ "epoch": 0.9332023575638507,
955
+ "grad_norm": 1.752038836479187,
956
+ "learning_rate": 9.949012603299404e-05,
957
+ "loss": 0.5919,
958
+ "mean_token_accuracy": 0.7839440703392029,
959
+ "num_tokens": 1308196.0,
960
+ "step": 950
961
+ },
962
+ {
963
+ "entropy": 1.3016840934753418,
964
+ "epoch": 0.9430255402750491,
965
+ "grad_norm": 1.8453019857406616,
966
+ "learning_rate": 9.946672833144097e-05,
967
+ "loss": 0.5754,
968
+ "mean_token_accuracy": 0.7904948055744171,
969
+ "num_tokens": 1322261.0,
970
+ "step": 960
971
+ },
972
+ {
973
+ "entropy": 1.2948450207710267,
974
+ "epoch": 0.9528487229862476,
975
+ "grad_norm": 1.617616891860962,
976
+ "learning_rate": 9.944280863075148e-05,
977
+ "loss": 0.5965,
978
+ "mean_token_accuracy": 0.7802974283695221,
979
+ "num_tokens": 1336225.0,
980
+ "step": 970
981
+ },
982
+ {
983
+ "entropy": 1.302824819087982,
984
+ "epoch": 0.962671905697446,
985
+ "grad_norm": 1.8175745010375977,
986
+ "learning_rate": 9.941836718333894e-05,
987
+ "loss": 0.6292,
988
+ "mean_token_accuracy": 0.7750960767269135,
989
+ "num_tokens": 1349509.0,
990
+ "step": 980
991
+ },
992
+ {
993
+ "entropy": 1.2981536149978639,
994
+ "epoch": 0.9724950884086444,
995
+ "grad_norm": 1.411348581314087,
996
+ "learning_rate": 9.939340424712247e-05,
997
+ "loss": 0.5127,
998
+ "mean_token_accuracy": 0.8160092115402222,
999
+ "num_tokens": 1363443.0,
1000
+ "step": 990
1001
+ },
1002
+ {
1003
+ "entropy": 1.321254277229309,
1004
+ "epoch": 0.9823182711198428,
1005
+ "grad_norm": 1.8093916177749634,
1006
+ "learning_rate": 9.936792008552418e-05,
1007
+ "loss": 0.6142,
1008
+ "mean_token_accuracy": 0.7801197230815887,
1009
+ "num_tokens": 1377815.0,
1010
+ "step": 1000
1011
+ },
1012
+ {
1013
+ "entropy": 1.2920042157173157,
1014
+ "epoch": 0.9921414538310412,
1015
+ "grad_norm": 2.154522657394409,
1016
+ "learning_rate": 9.934191496746647e-05,
1017
+ "loss": 0.5433,
1018
+ "mean_token_accuracy": 0.7936553716659546,
1019
+ "num_tokens": 1391706.0,
1020
+ "step": 1010
1021
+ },
1022
+ {
1023
+ "entropy": 1.3085604310035706,
1024
+ "epoch": 1.0019646365422397,
1025
+ "grad_norm": 1.887580394744873,
1026
+ "learning_rate": 9.931538916736911e-05,
1027
+ "loss": 0.5834,
1028
+ "mean_token_accuracy": 0.7798990666866302,
1029
+ "num_tokens": 1405013.0,
1030
+ "step": 1020
1031
+ },
1032
+ {
1033
+ "entropy": 1.2716426730155945,
1034
+ "epoch": 1.0117878192534382,
1035
+ "grad_norm": 2.3578274250030518,
1036
+ "learning_rate": 9.928834296514642e-05,
1037
+ "loss": 0.4712,
1038
+ "mean_token_accuracy": 0.8309662401676178,
1039
+ "num_tokens": 1418903.0,
1040
+ "step": 1030
1041
+ },
1042
+ {
1043
+ "entropy": 1.3070968985557556,
1044
+ "epoch": 1.0216110019646365,
1045
+ "grad_norm": 1.740882396697998,
1046
+ "learning_rate": 9.926077664620425e-05,
1047
+ "loss": 0.5571,
1048
+ "mean_token_accuracy": 0.8008412003517151,
1049
+ "num_tokens": 1432163.0,
1050
+ "step": 1040
1051
+ },
1052
+ {
1053
+ "entropy": 1.275494432449341,
1054
+ "epoch": 1.031434184675835,
1055
+ "grad_norm": 1.8797022104263306,
1056
+ "learning_rate": 9.923269050143702e-05,
1057
+ "loss": 0.513,
1058
+ "mean_token_accuracy": 0.8186901092529297,
1059
+ "num_tokens": 1445781.0,
1060
+ "step": 1050
1061
+ },
1062
+ {
1063
+ "entropy": 1.2804364919662476,
1064
+ "epoch": 1.0412573673870333,
1065
+ "grad_norm": 2.1894519329071045,
1066
+ "learning_rate": 9.920408482722461e-05,
1067
+ "loss": 0.5092,
1068
+ "mean_token_accuracy": 0.8133958995342254,
1069
+ "num_tokens": 1460380.0,
1070
+ "step": 1060
1071
+ },
1072
+ {
1073
+ "entropy": 1.2710145592689515,
1074
+ "epoch": 1.0510805500982319,
1075
+ "grad_norm": 3.175863742828369,
1076
+ "learning_rate": 9.917495992542925e-05,
1077
+ "loss": 0.5161,
1078
+ "mean_token_accuracy": 0.813822203874588,
1079
+ "num_tokens": 1474285.0,
1080
+ "step": 1070
1081
+ },
1082
+ {
1083
+ "entropy": 1.2840298771858216,
1084
+ "epoch": 1.0609037328094302,
1085
+ "grad_norm": 2.1368906497955322,
1086
+ "learning_rate": 9.914531610339235e-05,
1087
+ "loss": 0.5541,
1088
+ "mean_token_accuracy": 0.8022448778152466,
1089
+ "num_tokens": 1487669.0,
1090
+ "step": 1080
1091
+ },
1092
+ {
1093
+ "entropy": 1.2852188110351563,
1094
+ "epoch": 1.0707269155206287,
1095
+ "grad_norm": 2.0913002490997314,
1096
+ "learning_rate": 9.911515367393122e-05,
1097
+ "loss": 0.5708,
1098
+ "mean_token_accuracy": 0.8023091912269592,
1099
+ "num_tokens": 1501959.0,
1100
+ "step": 1090
1101
+ },
1102
+ {
1103
+ "entropy": 1.2778987884521484,
1104
+ "epoch": 1.080550098231827,
1105
+ "grad_norm": 2.210040807723999,
1106
+ "learning_rate": 9.908447295533583e-05,
1107
+ "loss": 0.5464,
1108
+ "mean_token_accuracy": 0.7970520079135894,
1109
+ "num_tokens": 1516171.0,
1110
+ "step": 1100
1111
+ },
1112
+ {
1113
+ "entropy": 1.236346960067749,
1114
+ "epoch": 1.0903732809430255,
1115
+ "grad_norm": 1.4377529621124268,
1116
+ "learning_rate": 9.905327427136535e-05,
1117
+ "loss": 0.4655,
1118
+ "mean_token_accuracy": 0.8350913822650909,
1119
+ "num_tokens": 1529474.0,
1120
+ "step": 1110
1121
+ },
1122
+ {
1123
+ "entropy": 1.267558765411377,
1124
+ "epoch": 1.1001964636542239,
1125
+ "grad_norm": 2.254699945449829,
1126
+ "learning_rate": 9.902155795124486e-05,
1127
+ "loss": 0.5446,
1128
+ "mean_token_accuracy": 0.8079259395599365,
1129
+ "num_tokens": 1543309.0,
1130
+ "step": 1120
1131
+ },
1132
+ {
1133
+ "entropy": 1.2463451504707337,
1134
+ "epoch": 1.1100196463654224,
1135
+ "grad_norm": 1.5955703258514404,
1136
+ "learning_rate": 9.898932432966174e-05,
1137
+ "loss": 0.4809,
1138
+ "mean_token_accuracy": 0.8256923139095307,
1139
+ "num_tokens": 1557446.0,
1140
+ "step": 1130
1141
+ },
1142
+ {
1143
+ "entropy": 1.248048484325409,
1144
+ "epoch": 1.119842829076621,
1145
+ "grad_norm": 1.6384292840957642,
1146
+ "learning_rate": 9.89565737467623e-05,
1147
+ "loss": 0.4743,
1148
+ "mean_token_accuracy": 0.8341399788856506,
1149
+ "num_tokens": 1571146.0,
1150
+ "step": 1140
1151
+ },
1152
+ {
1153
+ "entropy": 1.2607948899269104,
1154
+ "epoch": 1.1296660117878192,
1155
+ "grad_norm": 1.8771889209747314,
1156
+ "learning_rate": 9.892330654814803e-05,
1157
+ "loss": 0.5011,
1158
+ "mean_token_accuracy": 0.813750559091568,
1159
+ "num_tokens": 1585417.0,
1160
+ "step": 1150
1161
+ },
1162
+ {
1163
+ "entropy": 1.233643364906311,
1164
+ "epoch": 1.1394891944990178,
1165
+ "grad_norm": 2.2473816871643066,
1166
+ "learning_rate": 9.888952308487203e-05,
1167
+ "loss": 0.4554,
1168
+ "mean_token_accuracy": 0.8318858861923217,
1169
+ "num_tokens": 1598975.0,
1170
+ "step": 1160
1171
+ },
1172
+ {
1173
+ "entropy": 1.238119614124298,
1174
+ "epoch": 1.149312377210216,
1175
+ "grad_norm": 2.5443625450134277,
1176
+ "learning_rate": 9.885522371343532e-05,
1177
+ "loss": 0.4779,
1178
+ "mean_token_accuracy": 0.832828551530838,
1179
+ "num_tokens": 1612637.0,
1180
+ "step": 1170
1181
+ },
1182
+ {
1183
+ "entropy": 1.2466851353645325,
1184
+ "epoch": 1.1591355599214146,
1185
+ "grad_norm": 2.026611804962158,
1186
+ "learning_rate": 9.882040879578304e-05,
1187
+ "loss": 0.5372,
1188
+ "mean_token_accuracy": 0.805012685060501,
1189
+ "num_tokens": 1626057.0,
1190
+ "step": 1180
1191
+ },
1192
+ {
1193
+ "entropy": 1.2370510578155518,
1194
+ "epoch": 1.168958742632613,
1195
+ "grad_norm": 1.9643908739089966,
1196
+ "learning_rate": 9.878507869930067e-05,
1197
+ "loss": 0.4996,
1198
+ "mean_token_accuracy": 0.8205065846443176,
1199
+ "num_tokens": 1639457.0,
1200
+ "step": 1190
1201
+ },
1202
+ {
1203
+ "entropy": 1.2587358474731445,
1204
+ "epoch": 1.1787819253438114,
1205
+ "grad_norm": 2.439802646636963,
1206
+ "learning_rate": 9.874923379681009e-05,
1207
+ "loss": 0.5101,
1208
+ "mean_token_accuracy": 0.8154071569442749,
1209
+ "num_tokens": 1653028.0,
1210
+ "step": 1200
1211
+ },
1212
+ {
1213
+ "entropy": 1.245667052268982,
1214
+ "epoch": 1.1886051080550097,
1215
+ "grad_norm": 1.7865586280822754,
1216
+ "learning_rate": 9.871287446656574e-05,
1217
+ "loss": 0.4969,
1218
+ "mean_token_accuracy": 0.8192065060138702,
1219
+ "num_tokens": 1666720.0,
1220
+ "step": 1210
1221
+ },
1222
+ {
1223
+ "entropy": 1.2510582208633423,
1224
+ "epoch": 1.1984282907662083,
1225
+ "grad_norm": 2.783156633377075,
1226
+ "learning_rate": 9.867600109225052e-05,
1227
+ "loss": 0.5276,
1228
+ "mean_token_accuracy": 0.8083367943763733,
1229
+ "num_tokens": 1680530.0,
1230
+ "step": 1220
1231
+ },
1232
+ {
1233
+ "entropy": 1.2682287335395812,
1234
+ "epoch": 1.2082514734774068,
1235
+ "grad_norm": 2.4126596450805664,
1236
+ "learning_rate": 9.863861406297186e-05,
1237
+ "loss": 0.5983,
1238
+ "mean_token_accuracy": 0.7770793735980988,
1239
+ "num_tokens": 1694339.0,
1240
+ "step": 1230
1241
+ },
1242
+ {
1243
+ "entropy": 1.2660762786865234,
1244
+ "epoch": 1.218074656188605,
1245
+ "grad_norm": 1.9345526695251465,
1246
+ "learning_rate": 9.860071377325744e-05,
1247
+ "loss": 0.4965,
1248
+ "mean_token_accuracy": 0.8184070110321044,
1249
+ "num_tokens": 1708197.0,
1250
+ "step": 1240
1251
+ },
1252
+ {
1253
+ "entropy": 1.255600094795227,
1254
+ "epoch": 1.2278978388998034,
1255
+ "grad_norm": 2.6998202800750732,
1256
+ "learning_rate": 9.856230062305127e-05,
1257
+ "loss": 0.5139,
1258
+ "mean_token_accuracy": 0.8155104756355286,
1259
+ "num_tokens": 1722214.0,
1260
+ "step": 1250
1261
+ },
1262
+ {
1263
+ "entropy": 1.225659394264221,
1264
+ "epoch": 1.237721021611002,
1265
+ "grad_norm": 1.7819828987121582,
1266
+ "learning_rate": 9.852337501770923e-05,
1267
+ "loss": 0.4564,
1268
+ "mean_token_accuracy": 0.8367070078849792,
1269
+ "num_tokens": 1736088.0,
1270
+ "step": 1260
1271
+ },
1272
+ {
1273
+ "entropy": 1.2524644374847411,
1274
+ "epoch": 1.2475442043222005,
1275
+ "grad_norm": 1.3680812120437622,
1276
+ "learning_rate": 9.848393736799496e-05,
1277
+ "loss": 0.5215,
1278
+ "mean_token_accuracy": 0.808636051416397,
1279
+ "num_tokens": 1749496.0,
1280
+ "step": 1270
1281
+ },
1282
+ {
1283
+ "entropy": 1.257518184185028,
1284
+ "epoch": 1.2573673870333988,
1285
+ "grad_norm": 2.3655996322631836,
1286
+ "learning_rate": 9.844398809007545e-05,
1287
+ "loss": 0.5431,
1288
+ "mean_token_accuracy": 0.7984029889106751,
1289
+ "num_tokens": 1763423.0,
1290
+ "step": 1280
1291
+ },
1292
+ {
1293
+ "entropy": 1.2404034614562989,
1294
+ "epoch": 1.2671905697445973,
1295
+ "grad_norm": 2.355236053466797,
1296
+ "learning_rate": 9.840352760551663e-05,
1297
+ "loss": 0.5024,
1298
+ "mean_token_accuracy": 0.8227346181869507,
1299
+ "num_tokens": 1777421.0,
1300
+ "step": 1290
1301
+ },
1302
+ {
1303
+ "entropy": 1.2580087780952454,
1304
+ "epoch": 1.2770137524557956,
1305
+ "grad_norm": 2.0372347831726074,
1306
+ "learning_rate": 9.836255634127899e-05,
1307
+ "loss": 0.4846,
1308
+ "mean_token_accuracy": 0.8213749349117279,
1309
+ "num_tokens": 1792763.0,
1310
+ "step": 1300
1311
+ },
1312
+ {
1313
+ "entropy": 1.2565680623054505,
1314
+ "epoch": 1.2868369351669942,
1315
+ "grad_norm": 2.134438991546631,
1316
+ "learning_rate": 9.832107472971304e-05,
1317
+ "loss": 0.5592,
1318
+ "mean_token_accuracy": 0.7969561636447906,
1319
+ "num_tokens": 1806941.0,
1320
+ "step": 1310
1321
+ },
1322
+ {
1323
+ "entropy": 1.246485674381256,
1324
+ "epoch": 1.2966601178781925,
1325
+ "grad_norm": 2.4246816635131836,
1326
+ "learning_rate": 9.82790832085547e-05,
1327
+ "loss": 0.4951,
1328
+ "mean_token_accuracy": 0.82363041639328,
1329
+ "num_tokens": 1820836.0,
1330
+ "step": 1320
1331
+ },
1332
+ {
1333
+ "entropy": 1.2375126361846924,
1334
+ "epoch": 1.306483300589391,
1335
+ "grad_norm": 2.738617420196533,
1336
+ "learning_rate": 9.823658222092081e-05,
1337
+ "loss": 0.5006,
1338
+ "mean_token_accuracy": 0.8225988149642944,
1339
+ "num_tokens": 1833250.0,
1340
+ "step": 1330
1341
+ },
1342
+ {
1343
+ "entropy": 1.24787095785141,
1344
+ "epoch": 1.3163064833005893,
1345
+ "grad_norm": 1.8391460180282593,
1346
+ "learning_rate": 9.819357221530425e-05,
1347
+ "loss": 0.4972,
1348
+ "mean_token_accuracy": 0.8270265519618988,
1349
+ "num_tokens": 1847343.0,
1350
+ "step": 1340
1351
+ },
1352
+ {
1353
+ "entropy": 1.2579961180686952,
1354
+ "epoch": 1.3261296660117878,
1355
+ "grad_norm": 1.4534238576889038,
1356
+ "learning_rate": 9.815005364556946e-05,
1357
+ "loss": 0.4954,
1358
+ "mean_token_accuracy": 0.8219050347805024,
1359
+ "num_tokens": 1861600.0,
1360
+ "step": 1350
1361
+ },
1362
+ {
1363
+ "entropy": 1.2523591637611389,
1364
+ "epoch": 1.3359528487229864,
1365
+ "grad_norm": 2.286081075668335,
1366
+ "learning_rate": 9.810602697094742e-05,
1367
+ "loss": 0.528,
1368
+ "mean_token_accuracy": 0.8146000444889069,
1369
+ "num_tokens": 1875384.0,
1370
+ "step": 1360
1371
+ },
1372
+ {
1373
+ "entropy": 1.263988447189331,
1374
+ "epoch": 1.3457760314341847,
1375
+ "grad_norm": 1.7268867492675781,
1376
+ "learning_rate": 9.806149265603096e-05,
1377
+ "loss": 0.496,
1378
+ "mean_token_accuracy": 0.8314105927944183,
1379
+ "num_tokens": 1888118.0,
1380
+ "step": 1370
1381
+ },
1382
+ {
1383
+ "entropy": 1.2864573359489442,
1384
+ "epoch": 1.355599214145383,
1385
+ "grad_norm": 1.9473626613616943,
1386
+ "learning_rate": 9.801645117076972e-05,
1387
+ "loss": 0.6076,
1388
+ "mean_token_accuracy": 0.7793005406856537,
1389
+ "num_tokens": 1901478.0,
1390
+ "step": 1380
1391
+ },
1392
+ {
1393
+ "entropy": 1.2580334901809693,
1394
+ "epoch": 1.3654223968565815,
1395
+ "grad_norm": 2.5675950050354004,
1396
+ "learning_rate": 9.797090299046539e-05,
1397
+ "loss": 0.5201,
1398
+ "mean_token_accuracy": 0.814705616235733,
1399
+ "num_tokens": 1914649.0,
1400
+ "step": 1390
1401
+ },
1402
+ {
1403
+ "entropy": 1.2844634294509887,
1404
+ "epoch": 1.37524557956778,
1405
+ "grad_norm": 2.2183785438537598,
1406
+ "learning_rate": 9.792484859576648e-05,
1407
+ "loss": 0.5447,
1408
+ "mean_token_accuracy": 0.8052274882793427,
1409
+ "num_tokens": 1928074.0,
1410
+ "step": 1400
1411
+ },
1412
+ {
1413
+ "entropy": 1.2458331108093261,
1414
+ "epoch": 1.3850687622789783,
1415
+ "grad_norm": 1.9489785432815552,
1416
+ "learning_rate": 9.787828847266339e-05,
1417
+ "loss": 0.4804,
1418
+ "mean_token_accuracy": 0.829998356103897,
1419
+ "num_tokens": 1941149.0,
1420
+ "step": 1410
1421
+ },
1422
+ {
1423
+ "entropy": 1.2675795674324035,
1424
+ "epoch": 1.3948919449901769,
1425
+ "grad_norm": 2.2568233013153076,
1426
+ "learning_rate": 9.783122311248319e-05,
1427
+ "loss": 0.5462,
1428
+ "mean_token_accuracy": 0.802941232919693,
1429
+ "num_tokens": 1955165.0,
1430
+ "step": 1420
1431
+ },
1432
+ {
1433
+ "entropy": 1.2623451232910157,
1434
+ "epoch": 1.4047151277013752,
1435
+ "grad_norm": 1.9349223375320435,
1436
+ "learning_rate": 9.778365301188454e-05,
1437
+ "loss": 0.5319,
1438
+ "mean_token_accuracy": 0.8103811144828796,
1439
+ "num_tokens": 1968689.0,
1440
+ "step": 1430
1441
+ },
1442
+ {
1443
+ "entropy": 1.2589616417884826,
1444
+ "epoch": 1.4145383104125737,
1445
+ "grad_norm": 2.0692477226257324,
1446
+ "learning_rate": 9.773557867285232e-05,
1447
+ "loss": 0.5031,
1448
+ "mean_token_accuracy": 0.8202072083950043,
1449
+ "num_tokens": 1983147.0,
1450
+ "step": 1440
1451
+ },
1452
+ {
1453
+ "entropy": 1.2585302472114563,
1454
+ "epoch": 1.424361493123772,
1455
+ "grad_norm": 2.16162371635437,
1456
+ "learning_rate": 9.768700060269247e-05,
1457
+ "loss": 0.526,
1458
+ "mean_token_accuracy": 0.8141628861427307,
1459
+ "num_tokens": 1996929.0,
1460
+ "step": 1450
1461
+ },
1462
+ {
1463
+ "entropy": 1.2599245667457581,
1464
+ "epoch": 1.4341846758349706,
1465
+ "grad_norm": 2.063103437423706,
1466
+ "learning_rate": 9.763791931402652e-05,
1467
+ "loss": 0.4848,
1468
+ "mean_token_accuracy": 0.8278682291507721,
1469
+ "num_tokens": 2010715.0,
1470
+ "step": 1460
1471
+ },
1472
+ {
1473
+ "entropy": 1.266039752960205,
1474
+ "epoch": 1.4440078585461689,
1475
+ "grad_norm": 2.109372854232788,
1476
+ "learning_rate": 9.758833532478624e-05,
1477
+ "loss": 0.5816,
1478
+ "mean_token_accuracy": 0.7883775234222412,
1479
+ "num_tokens": 2024736.0,
1480
+ "step": 1470
1481
+ },
1482
+ {
1483
+ "entropy": 1.2680623173713683,
1484
+ "epoch": 1.4538310412573674,
1485
+ "grad_norm": 1.812806487083435,
1486
+ "learning_rate": 9.753824915820814e-05,
1487
+ "loss": 0.5118,
1488
+ "mean_token_accuracy": 0.8144886434078217,
1489
+ "num_tokens": 2038954.0,
1490
+ "step": 1480
1491
+ },
1492
+ {
1493
+ "entropy": 1.2589596390724183,
1494
+ "epoch": 1.463654223968566,
1495
+ "grad_norm": 1.6400179862976074,
1496
+ "learning_rate": 9.748766134282807e-05,
1497
+ "loss": 0.5195,
1498
+ "mean_token_accuracy": 0.807390421628952,
1499
+ "num_tokens": 2052331.0,
1500
+ "step": 1490
1501
+ },
1502
+ {
1503
+ "entropy": 1.244090747833252,
1504
+ "epoch": 1.4734774066797642,
1505
+ "grad_norm": 2.0556066036224365,
1506
+ "learning_rate": 9.743657241247542e-05,
1507
+ "loss": 0.4997,
1508
+ "mean_token_accuracy": 0.8174088597297668,
1509
+ "num_tokens": 2066530.0,
1510
+ "step": 1500
1511
+ },
1512
+ {
1513
+ "entropy": 1.250917875766754,
1514
+ "epoch": 1.4833005893909625,
1515
+ "grad_norm": 2.830498218536377,
1516
+ "learning_rate": 9.738498290626764e-05,
1517
+ "loss": 0.4585,
1518
+ "mean_token_accuracy": 0.8412882685661316,
1519
+ "num_tokens": 2079919.0,
1520
+ "step": 1510
1521
+ },
1522
+ {
1523
+ "entropy": 1.2326926350593568,
1524
+ "epoch": 1.493123772102161,
1525
+ "grad_norm": 1.8350157737731934,
1526
+ "learning_rate": 9.733289336860458e-05,
1527
+ "loss": 0.5094,
1528
+ "mean_token_accuracy": 0.8157238185405731,
1529
+ "num_tokens": 2094074.0,
1530
+ "step": 1520
1531
+ },
1532
+ {
1533
+ "entropy": 1.2600191235542297,
1534
+ "epoch": 1.5029469548133596,
1535
+ "grad_norm": 1.993652105331421,
1536
+ "learning_rate": 9.728030434916266e-05,
1537
+ "loss": 0.5491,
1538
+ "mean_token_accuracy": 0.8047675967216492,
1539
+ "num_tokens": 2107458.0,
1540
+ "step": 1530
1541
+ },
1542
+ {
1543
+ "entropy": 1.259787654876709,
1544
+ "epoch": 1.512770137524558,
1545
+ "grad_norm": 2.0996932983398438,
1546
+ "learning_rate": 9.722721640288905e-05,
1547
+ "loss": 0.4725,
1548
+ "mean_token_accuracy": 0.8254640996456146,
1549
+ "num_tokens": 2121435.0,
1550
+ "step": 1540
1551
+ },
1552
+ {
1553
+ "entropy": 1.2564135551452638,
1554
+ "epoch": 1.5225933202357562,
1555
+ "grad_norm": 2.216902494430542,
1556
+ "learning_rate": 9.717363008999594e-05,
1557
+ "loss": 0.6043,
1558
+ "mean_token_accuracy": 0.7789163291454315,
1559
+ "num_tokens": 2134901.0,
1560
+ "step": 1550
1561
+ },
1562
+ {
1563
+ "entropy": 1.2386685490608216,
1564
+ "epoch": 1.5324165029469548,
1565
+ "grad_norm": 1.8616433143615723,
1566
+ "learning_rate": 9.711954597595446e-05,
1567
+ "loss": 0.4516,
1568
+ "mean_token_accuracy": 0.8284256815910339,
1569
+ "num_tokens": 2149157.0,
1570
+ "step": 1560
1571
+ },
1572
+ {
1573
+ "entropy": 1.2334220647811889,
1574
+ "epoch": 1.5422396856581533,
1575
+ "grad_norm": 2.008178234100342,
1576
+ "learning_rate": 9.706496463148888e-05,
1577
+ "loss": 0.484,
1578
+ "mean_token_accuracy": 0.82932368516922,
1579
+ "num_tokens": 2162991.0,
1580
+ "step": 1570
1581
+ },
1582
+ {
1583
+ "entropy": 1.2665512442588807,
1584
+ "epoch": 1.5520628683693518,
1585
+ "grad_norm": 2.1565146446228027,
1586
+ "learning_rate": 9.700988663257047e-05,
1587
+ "loss": 0.5353,
1588
+ "mean_token_accuracy": 0.8073971390724182,
1589
+ "num_tokens": 2177097.0,
1590
+ "step": 1580
1591
+ },
1592
+ {
1593
+ "entropy": 1.2624645590782166,
1594
+ "epoch": 1.5618860510805501,
1595
+ "grad_norm": 2.7686235904693604,
1596
+ "learning_rate": 9.695431256041147e-05,
1597
+ "loss": 0.5696,
1598
+ "mean_token_accuracy": 0.7965208232402802,
1599
+ "num_tokens": 2190589.0,
1600
+ "step": 1590
1601
+ },
1602
+ {
1603
+ "entropy": 1.254404366016388,
1604
+ "epoch": 1.5717092337917484,
1605
+ "grad_norm": 1.9496175050735474,
1606
+ "learning_rate": 9.689824300145893e-05,
1607
+ "loss": 0.5218,
1608
+ "mean_token_accuracy": 0.8181787610054017,
1609
+ "num_tokens": 2204358.0,
1610
+ "step": 1600
1611
+ },
1612
+ {
1613
+ "entropy": 1.2377846360206604,
1614
+ "epoch": 1.581532416502947,
1615
+ "grad_norm": 2.1385841369628906,
1616
+ "learning_rate": 9.684167854738857e-05,
1617
+ "loss": 0.4952,
1618
+ "mean_token_accuracy": 0.8231679797172546,
1619
+ "num_tokens": 2218080.0,
1620
+ "step": 1610
1621
+ },
1622
+ {
1623
+ "entropy": 1.2657816886901856,
1624
+ "epoch": 1.5913555992141455,
1625
+ "grad_norm": 1.9250800609588623,
1626
+ "learning_rate": 9.678461979509849e-05,
1627
+ "loss": 0.5684,
1628
+ "mean_token_accuracy": 0.796778404712677,
1629
+ "num_tokens": 2231436.0,
1630
+ "step": 1620
1631
+ },
1632
+ {
1633
+ "entropy": 1.2508048176765443,
1634
+ "epoch": 1.6011787819253438,
1635
+ "grad_norm": 2.177400827407837,
1636
+ "learning_rate": 9.672706734670289e-05,
1637
+ "loss": 0.4848,
1638
+ "mean_token_accuracy": 0.8291748940944672,
1639
+ "num_tokens": 2245613.0,
1640
+ "step": 1630
1641
+ },
1642
+ {
1643
+ "entropy": 1.268570113182068,
1644
+ "epoch": 1.611001964636542,
1645
+ "grad_norm": 2.31485652923584,
1646
+ "learning_rate": 9.66690218095257e-05,
1647
+ "loss": 0.5673,
1648
+ "mean_token_accuracy": 0.7923191308975219,
1649
+ "num_tokens": 2259056.0,
1650
+ "step": 1640
1651
+ },
1652
+ {
1653
+ "entropy": 1.2469953656196595,
1654
+ "epoch": 1.6208251473477406,
1655
+ "grad_norm": 2.7683792114257812,
1656
+ "learning_rate": 9.661048379609418e-05,
1657
+ "loss": 0.4902,
1658
+ "mean_token_accuracy": 0.8232687532901763,
1659
+ "num_tokens": 2272855.0,
1660
+ "step": 1650
1661
+ },
1662
+ {
1663
+ "entropy": 1.2610564589500428,
1664
+ "epoch": 1.6306483300589392,
1665
+ "grad_norm": 2.1523454189300537,
1666
+ "learning_rate": 9.655145392413251e-05,
1667
+ "loss": 0.5459,
1668
+ "mean_token_accuracy": 0.800895380973816,
1669
+ "num_tokens": 2286678.0,
1670
+ "step": 1660
1671
+ },
1672
+ {
1673
+ "entropy": 1.2304104089736938,
1674
+ "epoch": 1.6404715127701375,
1675
+ "grad_norm": 2.4282095432281494,
1676
+ "learning_rate": 9.649193281655518e-05,
1677
+ "loss": 0.4966,
1678
+ "mean_token_accuracy": 0.8258331537246704,
1679
+ "num_tokens": 2299799.0,
1680
+ "step": 1670
1681
+ },
1682
+ {
1683
+ "entropy": 1.2416871786117554,
1684
+ "epoch": 1.650294695481336,
1685
+ "grad_norm": 2.069984197616577,
1686
+ "learning_rate": 9.643192110146044e-05,
1687
+ "loss": 0.4981,
1688
+ "mean_token_accuracy": 0.8195957362651825,
1689
+ "num_tokens": 2314237.0,
1690
+ "step": 1680
1691
+ },
1692
+ {
1693
+ "entropy": 1.2401619911193849,
1694
+ "epoch": 1.6601178781925343,
1695
+ "grad_norm": 2.3762688636779785,
1696
+ "learning_rate": 9.637141941212374e-05,
1697
+ "loss": 0.5294,
1698
+ "mean_token_accuracy": 0.8102250933647156,
1699
+ "num_tokens": 2327772.0,
1700
+ "step": 1690
1701
+ },
1702
+ {
1703
+ "entropy": 1.2495620012283326,
1704
+ "epoch": 1.6699410609037328,
1705
+ "grad_norm": 2.802684783935547,
1706
+ "learning_rate": 9.631042838699096e-05,
1707
+ "loss": 0.5473,
1708
+ "mean_token_accuracy": 0.8017067730426788,
1709
+ "num_tokens": 2341503.0,
1710
+ "step": 1700
1711
+ },
1712
+ {
1713
+ "entropy": 1.2424279928207398,
1714
+ "epoch": 1.6797642436149314,
1715
+ "grad_norm": 1.5717180967330933,
1716
+ "learning_rate": 9.624894866967174e-05,
1717
+ "loss": 0.5288,
1718
+ "mean_token_accuracy": 0.8105488240718841,
1719
+ "num_tokens": 2355368.0,
1720
+ "step": 1710
1721
+ },
1722
+ {
1723
+ "entropy": 1.241310751438141,
1724
+ "epoch": 1.6895874263261297,
1725
+ "grad_norm": 2.1303505897521973,
1726
+ "learning_rate": 9.618698090893263e-05,
1727
+ "loss": 0.5075,
1728
+ "mean_token_accuracy": 0.8153672814369202,
1729
+ "num_tokens": 2369658.0,
1730
+ "step": 1720
1731
+ },
1732
+ {
1733
+ "entropy": 1.2365522384643555,
1734
+ "epoch": 1.699410609037328,
1735
+ "grad_norm": 2.0560405254364014,
1736
+ "learning_rate": 9.612452575869028e-05,
1737
+ "loss": 0.5393,
1738
+ "mean_token_accuracy": 0.7969626665115357,
1739
+ "num_tokens": 2382990.0,
1740
+ "step": 1730
1741
+ },
1742
+ {
1743
+ "entropy": 1.2362038850784303,
1744
+ "epoch": 1.7092337917485265,
1745
+ "grad_norm": 1.9128539562225342,
1746
+ "learning_rate": 9.606158387800454e-05,
1747
+ "loss": 0.5047,
1748
+ "mean_token_accuracy": 0.8211510121822357,
1749
+ "num_tokens": 2396917.0,
1750
+ "step": 1740
1751
+ },
1752
+ {
1753
+ "entropy": 1.2453686594963074,
1754
+ "epoch": 1.719056974459725,
1755
+ "grad_norm": 3.0778567790985107,
1756
+ "learning_rate": 9.599815593107153e-05,
1757
+ "loss": 0.5262,
1758
+ "mean_token_accuracy": 0.8054801046848297,
1759
+ "num_tokens": 2410056.0,
1760
+ "step": 1750
1761
+ },
1762
+ {
1763
+ "entropy": 1.241734540462494,
1764
+ "epoch": 1.7288801571709234,
1765
+ "grad_norm": 2.05613112449646,
1766
+ "learning_rate": 9.593424258721653e-05,
1767
+ "loss": 0.4914,
1768
+ "mean_token_accuracy": 0.8227891206741333,
1769
+ "num_tokens": 2423604.0,
1770
+ "step": 1760
1771
+ },
1772
+ {
1773
+ "entropy": 1.2589903235435487,
1774
+ "epoch": 1.7387033398821217,
1775
+ "grad_norm": 2.131194829940796,
1776
+ "learning_rate": 9.586984452088703e-05,
1777
+ "loss": 0.5733,
1778
+ "mean_token_accuracy": 0.7925102472305298,
1779
+ "num_tokens": 2437290.0,
1780
+ "step": 1770
1781
+ },
1782
+ {
1783
+ "entropy": 1.2547675371170044,
1784
+ "epoch": 1.7485265225933202,
1785
+ "grad_norm": 2.7211906909942627,
1786
+ "learning_rate": 9.580496241164556e-05,
1787
+ "loss": 0.5272,
1788
+ "mean_token_accuracy": 0.8076090633869171,
1789
+ "num_tokens": 2450587.0,
1790
+ "step": 1780
1791
+ },
1792
+ {
1793
+ "entropy": 1.2483873605728149,
1794
+ "epoch": 1.7583497053045187,
1795
+ "grad_norm": 2.1691336631774902,
1796
+ "learning_rate": 9.573959694416253e-05,
1797
+ "loss": 0.4981,
1798
+ "mean_token_accuracy": 0.8250246226787568,
1799
+ "num_tokens": 2464803.0,
1800
+ "step": 1790
1801
+ },
1802
+ {
1803
+ "entropy": 1.2557496905326844,
1804
+ "epoch": 1.768172888015717,
1805
+ "grad_norm": 2.1679351329803467,
1806
+ "learning_rate": 9.567374880820898e-05,
1807
+ "loss": 0.5053,
1808
+ "mean_token_accuracy": 0.8208329737186432,
1809
+ "num_tokens": 2478469.0,
1810
+ "step": 1800
1811
+ },
1812
+ {
1813
+ "entropy": 1.2435495257377625,
1814
+ "epoch": 1.7779960707269156,
1815
+ "grad_norm": 2.2118451595306396,
1816
+ "learning_rate": 9.560741869864938e-05,
1817
+ "loss": 0.4678,
1818
+ "mean_token_accuracy": 0.8377247154712677,
1819
+ "num_tokens": 2492183.0,
1820
+ "step": 1810
1821
+ },
1822
+ {
1823
+ "entropy": 1.227329707145691,
1824
+ "epoch": 1.7878192534381139,
1825
+ "grad_norm": 2.1643288135528564,
1826
+ "learning_rate": 9.554060731543415e-05,
1827
+ "loss": 0.4651,
1828
+ "mean_token_accuracy": 0.8346364259719848,
1829
+ "num_tokens": 2505870.0,
1830
+ "step": 1820
1831
+ },
1832
+ {
1833
+ "entropy": 1.2532490849494935,
1834
+ "epoch": 1.7976424361493124,
1835
+ "grad_norm": 1.8303252458572388,
1836
+ "learning_rate": 9.547331536359247e-05,
1837
+ "loss": 0.5014,
1838
+ "mean_token_accuracy": 0.8197422027587891,
1839
+ "num_tokens": 2520024.0,
1840
+ "step": 1830
1841
+ },
1842
+ {
1843
+ "entropy": 1.271022343635559,
1844
+ "epoch": 1.807465618860511,
1845
+ "grad_norm": 2.9909262657165527,
1846
+ "learning_rate": 9.540554355322466e-05,
1847
+ "loss": 0.4949,
1848
+ "mean_token_accuracy": 0.8201545178890228,
1849
+ "num_tokens": 2533689.0,
1850
+ "step": 1840
1851
+ },
1852
+ {
1853
+ "entropy": 1.2634048223495484,
1854
+ "epoch": 1.8172888015717092,
1855
+ "grad_norm": 1.7734454870224,
1856
+ "learning_rate": 9.533729259949478e-05,
1857
+ "loss": 0.5399,
1858
+ "mean_token_accuracy": 0.8053711652755737,
1859
+ "num_tokens": 2547528.0,
1860
+ "step": 1850
1861
+ },
1862
+ {
1863
+ "entropy": 1.290783977508545,
1864
+ "epoch": 1.8271119842829076,
1865
+ "grad_norm": 2.2786009311676025,
1866
+ "learning_rate": 9.526856322262308e-05,
1867
+ "loss": 0.5792,
1868
+ "mean_token_accuracy": 0.7914485156536102,
1869
+ "num_tokens": 2561664.0,
1870
+ "step": 1860
1871
+ },
1872
+ {
1873
+ "entropy": 1.2498828649520874,
1874
+ "epoch": 1.836935166994106,
1875
+ "grad_norm": 2.993764638900757,
1876
+ "learning_rate": 9.519935614787837e-05,
1877
+ "loss": 0.5043,
1878
+ "mean_token_accuracy": 0.8198988556861877,
1879
+ "num_tokens": 2575398.0,
1880
+ "step": 1870
1881
+ },
1882
+ {
1883
+ "entropy": 1.2753949642181397,
1884
+ "epoch": 1.8467583497053046,
1885
+ "grad_norm": 2.466764211654663,
1886
+ "learning_rate": 9.512967210557038e-05,
1887
+ "loss": 0.5359,
1888
+ "mean_token_accuracy": 0.8064365327358246,
1889
+ "num_tokens": 2589001.0,
1890
+ "step": 1880
1891
+ },
1892
+ {
1893
+ "entropy": 1.2798161029815673,
1894
+ "epoch": 1.856581532416503,
1895
+ "grad_norm": 1.6539644002914429,
1896
+ "learning_rate": 9.505951183104207e-05,
1897
+ "loss": 0.5409,
1898
+ "mean_token_accuracy": 0.8036971032619477,
1899
+ "num_tokens": 2602056.0,
1900
+ "step": 1890
1901
+ },
1902
+ {
1903
+ "entropy": 1.247439169883728,
1904
+ "epoch": 1.8664047151277012,
1905
+ "grad_norm": 2.616790533065796,
1906
+ "learning_rate": 9.498887606466182e-05,
1907
+ "loss": 0.4817,
1908
+ "mean_token_accuracy": 0.8258330225944519,
1909
+ "num_tokens": 2616334.0,
1910
+ "step": 1900
1911
+ },
1912
+ {
1913
+ "entropy": 1.2620904803276063,
1914
+ "epoch": 1.8762278978388998,
1915
+ "grad_norm": 2.2307326793670654,
1916
+ "learning_rate": 9.49177655518157e-05,
1917
+ "loss": 0.5128,
1918
+ "mean_token_accuracy": 0.8172138810157776,
1919
+ "num_tokens": 2630707.0,
1920
+ "step": 1910
1921
+ },
1922
+ {
1923
+ "entropy": 1.280482542514801,
1924
+ "epoch": 1.8860510805500983,
1925
+ "grad_norm": 2.6325061321258545,
1926
+ "learning_rate": 9.484618104289952e-05,
1927
+ "loss": 0.5774,
1928
+ "mean_token_accuracy": 0.7905748307704925,
1929
+ "num_tokens": 2644746.0,
1930
+ "step": 1920
1931
+ },
1932
+ {
1933
+ "entropy": 1.2566339731216432,
1934
+ "epoch": 1.8958742632612968,
1935
+ "grad_norm": 2.277913808822632,
1936
+ "learning_rate": 9.4774123293311e-05,
1937
+ "loss": 0.5013,
1938
+ "mean_token_accuracy": 0.8227693378925324,
1939
+ "num_tokens": 2658986.0,
1940
+ "step": 1930
1941
+ },
1942
+ {
1943
+ "entropy": 1.2552205681800843,
1944
+ "epoch": 1.9056974459724951,
1945
+ "grad_norm": 3.0060858726501465,
1946
+ "learning_rate": 9.470159306344165e-05,
1947
+ "loss": 0.511,
1948
+ "mean_token_accuracy": 0.817187237739563,
1949
+ "num_tokens": 2672385.0,
1950
+ "step": 1940
1951
+ },
1952
+ {
1953
+ "entropy": 1.2724160313606263,
1954
+ "epoch": 1.9155206286836934,
1955
+ "grad_norm": 2.1056430339813232,
1956
+ "learning_rate": 9.462859111866891e-05,
1957
+ "loss": 0.5097,
1958
+ "mean_token_accuracy": 0.8144063234329224,
1959
+ "num_tokens": 2686315.0,
1960
+ "step": 1950
1961
+ },
1962
+ {
1963
+ "entropy": 1.2793522596359252,
1964
+ "epoch": 1.925343811394892,
1965
+ "grad_norm": 2.075453519821167,
1966
+ "learning_rate": 9.455511822934802e-05,
1967
+ "loss": 0.5414,
1968
+ "mean_token_accuracy": 0.8034018754959107,
1969
+ "num_tokens": 2700223.0,
1970
+ "step": 1960
1971
+ },
1972
+ {
1973
+ "entropy": 1.2614792227745055,
1974
+ "epoch": 1.9351669941060905,
1975
+ "grad_norm": 2.2977967262268066,
1976
+ "learning_rate": 9.448117517080383e-05,
1977
+ "loss": 0.4827,
1978
+ "mean_token_accuracy": 0.8254502475261688,
1979
+ "num_tokens": 2714485.0,
1980
+ "step": 1970
1981
+ },
1982
+ {
1983
+ "entropy": 1.2860048413276672,
1984
+ "epoch": 1.9449901768172888,
1985
+ "grad_norm": 1.679022192955017,
1986
+ "learning_rate": 9.44067627233227e-05,
1987
+ "loss": 0.5495,
1988
+ "mean_token_accuracy": 0.8007942914962769,
1989
+ "num_tokens": 2727978.0,
1990
+ "step": 1980
1991
+ },
1992
+ {
1993
+ "entropy": 1.2813897252082824,
1994
+ "epoch": 1.9548133595284871,
1995
+ "grad_norm": 2.2625648975372314,
1996
+ "learning_rate": 9.433188167214419e-05,
1997
+ "loss": 0.5245,
1998
+ "mean_token_accuracy": 0.8010579526424408,
1999
+ "num_tokens": 2742267.0,
2000
+ "step": 1990
2001
+ },
2002
+ {
2003
+ "entropy": 1.2723148226737977,
2004
+ "epoch": 1.9646365422396856,
2005
+ "grad_norm": 1.6450095176696777,
2006
+ "learning_rate": 9.425653280745289e-05,
2007
+ "loss": 0.5382,
2008
+ "mean_token_accuracy": 0.8019434869289398,
2009
+ "num_tokens": 2755781.0,
2010
+ "step": 2000
2011
+ },
2012
+ {
2013
+ "entropy": 1.252918040752411,
2014
+ "epoch": 1.9744597249508842,
2015
+ "grad_norm": 2.664660692214966,
2016
+ "learning_rate": 9.418071692436991e-05,
2017
+ "loss": 0.4686,
2018
+ "mean_token_accuracy": 0.834530645608902,
2019
+ "num_tokens": 2769364.0,
2020
+ "step": 2010
2021
+ },
2022
+ {
2023
+ "entropy": 1.2819023251533508,
2024
+ "epoch": 1.9842829076620825,
2025
+ "grad_norm": 2.215744972229004,
2026
+ "learning_rate": 9.410443482294468e-05,
2027
+ "loss": 0.5552,
2028
+ "mean_token_accuracy": 0.802883917093277,
2029
+ "num_tokens": 2782778.0,
2030
+ "step": 2020
2031
+ },
2032
+ {
2033
+ "entropy": 1.2668519973754884,
2034
+ "epoch": 1.9941060903732808,
2035
+ "grad_norm": 1.973852276802063,
2036
+ "learning_rate": 9.402768730814632e-05,
2037
+ "loss": 0.4683,
2038
+ "mean_token_accuracy": 0.8320684492588043,
2039
+ "num_tokens": 2796370.0,
2040
+ "step": 2030
2041
+ }
2042
+ ],
2043
+ "logging_steps": 10,
2044
+ "max_steps": 10180,
2045
+ "num_input_tokens_seen": 0,
2046
+ "num_train_epochs": 10,
2047
+ "save_steps": 500,
2048
+ "stateful_callbacks": {
2049
+ "TrainerControl": {
2050
+ "args": {
2051
+ "should_epoch_stop": false,
2052
+ "should_evaluate": false,
2053
+ "should_log": false,
2054
+ "should_save": true,
2055
+ "should_training_stop": false
2056
+ },
2057
+ "attributes": {}
2058
+ }
2059
+ },
2060
+ "total_flos": 1.1930547557440512e+17,
2061
+ "train_batch_size": 8,
2062
+ "trial_name": null,
2063
+ "trial_params": null
2064
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca00661b4201b9c900ba613719f42e2216580f8bd1d0e3994cb00560554804cf
3
+ size 6481
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-2036/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/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": "Qwen/Qwen2.5-7B-Instruct",
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
+ "v_proj",
36
+ "o_proj",
37
+ "up_proj",
38
+ "q_proj",
39
+ "k_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/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4874ce4daecc23f55bfbb117c7ac489e347cad968b9e42a2044a48a6b4dac404
3
+ size 80792096
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
checkpoints/cat_qwen25_7b_r8_a32_adamw_e10_lr1e-4_s1_vt_add_a0.5_B3_ALL_atag_noSys/checkpoint-3054/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
3
+ size 11421896