darwinkernelpanic commited on
Commit
7d183de
·
verified ·
1 Parent(s): a4558e3

Add files using upload-large-folder tool

Browse files
Files changed (39) hide show
  1. README.md +164 -0
  2. adapter_model.safetensors +2 -2
  3. checkpoint-2000/README.md +208 -0
  4. checkpoint-2000/adapter_config.json +43 -0
  5. checkpoint-2000/adapter_model.safetensors +3 -0
  6. checkpoint-2000/chat_template.jinja +5 -0
  7. checkpoint-2000/optimizer.pt +3 -0
  8. checkpoint-2000/rng_state.pth +3 -0
  9. checkpoint-2000/scheduler.pt +3 -0
  10. checkpoint-2000/special_tokens_map.json +24 -0
  11. checkpoint-2000/tokenizer.model +3 -0
  12. checkpoint-2000/tokenizer_config.json +44 -0
  13. checkpoint-2000/trainer_state.json +1110 -0
  14. checkpoint-2000/training_args.bin +3 -0
  15. checkpoint-3000/README.md +208 -0
  16. checkpoint-3000/adapter_config.json +43 -0
  17. checkpoint-3000/adapter_model.safetensors +3 -0
  18. checkpoint-3000/chat_template.jinja +5 -0
  19. checkpoint-3000/optimizer.pt +3 -0
  20. checkpoint-3000/rng_state.pth +3 -0
  21. checkpoint-3000/scheduler.pt +3 -0
  22. checkpoint-3000/special_tokens_map.json +24 -0
  23. checkpoint-3000/tokenizer.model +3 -0
  24. checkpoint-3000/tokenizer_config.json +44 -0
  25. checkpoint-3000/trainer_state.json +1642 -0
  26. checkpoint-3000/training_args.bin +3 -0
  27. checkpoint-3996/README.md +208 -0
  28. checkpoint-3996/adapter_config.json +43 -0
  29. checkpoint-3996/adapter_model.safetensors +3 -0
  30. checkpoint-3996/chat_template.jinja +5 -0
  31. checkpoint-3996/optimizer.pt +3 -0
  32. checkpoint-3996/rng_state.pth +3 -0
  33. checkpoint-3996/scheduler.pt +3 -0
  34. checkpoint-3996/special_tokens_map.json +24 -0
  35. checkpoint-3996/tokenizer.model +3 -0
  36. checkpoint-3996/tokenizer_config.json +44 -0
  37. checkpoint-3996/trainer_state.json +2149 -0
  38. checkpoint-3996/training_args.bin +3 -0
  39. debug.log +0 -0
README.md ADDED
@@ -0,0 +1,164 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: llama2
4
+ base_model: codellama/CodeLlama-7b-hf
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:codellama/CodeLlama-7b-hf
8
+ - lora
9
+ - transformers
10
+ datasets:
11
+ - darwinkernelpanic/luau-reasoning-normalized
12
+ pipeline_tag: text-generation
13
+ model-index:
14
+ - name: outputs/luau-codellama-h200-fast
15
+ results: []
16
+ ---
17
+
18
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
19
+ should probably proofread and complete it, then remove this comment. -->
20
+
21
+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
22
+ <details><summary>See axolotl config</summary>
23
+
24
+ axolotl version: `0.13.0.dev0`
25
+ ```yaml
26
+ base_model: codellama/CodeLlama-7b-hf
27
+ model_type: LlamaForCausalLM
28
+ tokenizer_type: LlamaTokenizer
29
+
30
+ # Keep full precision weights (fast on Hopper)
31
+ load_in_8bit: false
32
+ load_in_4bit: false
33
+ strict: false
34
+
35
+ chat_template: llama3
36
+
37
+ datasets:
38
+ - path: darwinkernelpanic/luau-reasoning-normalized
39
+ type: chat_template
40
+ conversation: llama3
41
+ field_messages: messages
42
+ add_generation_prompt: true
43
+
44
+ # Preprocessing workers (CPU). Fine as-is.
45
+ num_proc: 16
46
+
47
+ output_dir: ./outputs/luau-codellama-h200-fast
48
+
49
+ # ===== LoRA =====
50
+ adapter: lora
51
+ lora_r: 16
52
+ lora_alpha: 32
53
+ lora_dropout: 0.05
54
+ lora_target_modules:
55
+ - q_proj
56
+ - k_proj
57
+ - v_proj
58
+ - o_proj
59
+
60
+ # ===== Precision =====
61
+ bf16: true
62
+ fp16: false
63
+ tf32: true
64
+
65
+ # ===== Sequence / batching =====
66
+ sequence_len: 4096
67
+ # Keep packing for throughput, but enable length grouping to cut padding
68
+ sample_packing: true
69
+ group_by_length: true
70
+
71
+ # Lower micro-batch a bit to kill peak VRAM while staying fast
72
+ micro_batch_size: 5
73
+ gradient_accumulation_steps: 1
74
+
75
+ # ===== Training =====
76
+ num_epochs: 3
77
+ optimizer: adamw_torch
78
+ learning_rate: 2e-4
79
+ lr_scheduler_type: cosine
80
+ warmup_steps: 100
81
+
82
+ train_on_inputs: false
83
+
84
+ # Turn on checkpointing — tiny speed hit, big memory win
85
+ gradient_checkpointing: true
86
+ gradient_clipping: 1.0
87
+
88
+ # ===== Dataloader =====
89
+ # Keep pin_memory, but avoid too many loader workers in Accelerate
90
+ dataloader_num_workers: 2
91
+ dataloader_pin_memory: true
92
+ # Optional: avoid insanely large host->device prefetch
93
+ # dataloader_prefetch_factor: 2
94
+
95
+ # ===== Logging / eval =====
96
+ logging_steps: 25
97
+ val_set_size: 0.05
98
+ # Reduce eval/save frequency to avoid spikes
99
+ eval_steps: 1000
100
+ save_strategy: steps
101
+ save_steps: 1000
102
+ save_total_limit: 3
103
+
104
+ seed: 42
105
+
106
+ # ===== DeepSpeed =====
107
+ # Off for single H200 — overhead not worth it for 7B
108
+ ```
109
+
110
+ </details><br>
111
+
112
+ # outputs/luau-codellama-h200-fast
113
+
114
+ This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the darwinkernelpanic/luau-reasoning-normalized dataset.
115
+ It achieves the following results on the evaluation set:
116
+ - Loss: 0.4927
117
+ - Ppl: 1.6368
118
+ - Memory/max Active (gib): 19.1
119
+ - Memory/max Allocated (gib): 19.1
120
+ - Memory/device Reserved (gib): 139.06
121
+
122
+ ## Model description
123
+
124
+ More information needed
125
+
126
+ ## Intended uses & limitations
127
+
128
+ More information needed
129
+
130
+ ## Training and evaluation data
131
+
132
+ More information needed
133
+
134
+ ## Training procedure
135
+
136
+ ### Training hyperparameters
137
+
138
+ The following hyperparameters were used during training:
139
+ - learning_rate: 0.0002
140
+ - train_batch_size: 5
141
+ - eval_batch_size: 5
142
+ - seed: 42
143
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
144
+ - lr_scheduler_type: cosine
145
+ - lr_scheduler_warmup_steps: 100
146
+ - training_steps: 3996
147
+
148
+ ### Training results
149
+
150
+ | Training Loss | Epoch | Step | Validation Loss | Ppl | Active (gib) | Allocated (gib) | Reserved (gib) |
151
+ |:-------------:|:------:|:----:|:---------------:|:------:|:------------:|:---------------:|:--------------:|
152
+ | No log | 0 | 0 | 1.6888 | 5.4129 | 18.94 | 18.94 | 139.12 |
153
+ | 0.5511 | 0.7502 | 1000 | 0.5410 | 1.7177 | 19.1 | 19.1 | 139.02 |
154
+ | 0.5052 | 1.5004 | 2000 | 0.5064 | 1.6593 | 19.1 | 19.1 | 139.06 |
155
+ | 0.4733 | 2.2506 | 3000 | 0.4927 | 1.6368 | 19.1 | 19.1 | 139.06 |
156
+
157
+
158
+ ### Framework versions
159
+
160
+ - PEFT 0.18.0
161
+ - Transformers 4.57.1
162
+ - Pytorch 2.8.0+cu128
163
+ - Datasets 4.4.1
164
+ - Tokenizers 0.22.1
adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5435b9255c61a5d527452354bcf1f8d19766555d80a880c8058888a3d14d32e4
3
- size 33589040
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:117f1345e5c50f25128a7a46faf63217f9c93561ea40a0465fc49fe91eab762a
3
+ size 67143296
checkpoint-2000/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: codellama/CodeLlama-7b-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:codellama/CodeLlama-7b-hf
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- 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. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ 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).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.18.0
checkpoint-2000/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "codellama/CodeLlama-7b-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
9
+ "ensure_weight_tying": false,
10
+ "eva_config": null,
11
+ "exclude_modules": null,
12
+ "fan_in_fan_out": null,
13
+ "inference_mode": true,
14
+ "init_lora_weights": true,
15
+ "layer_replication": null,
16
+ "layers_pattern": null,
17
+ "layers_to_transform": null,
18
+ "loftq_config": {},
19
+ "lora_alpha": 32,
20
+ "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
+ "megatron_config": null,
23
+ "megatron_core": "megatron.core",
24
+ "modules_to_save": null,
25
+ "peft_type": "LORA",
26
+ "peft_version": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "o_proj",
33
+ "v_proj",
34
+ "k_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": [],
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-2000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66a52b1a3b7e275e6ca6a1b4e9c618cadb590db898823dfe8668c304684e5b78
3
+ size 67143296
checkpoint-2000/chat_template.jinja ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
2
+
3
+ '+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
4
+
5
+ ' }}{% endif %}
checkpoint-2000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:42575df9ba3d20ffae7081ec06b874a4a485aef3188b2c57e317c3014149df80
3
+ size 134433995
checkpoint-2000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6dd1989f8fb25657391bdb38e58849515e95e29f553d1fb6f5355a4baca32f48
3
+ size 14645
checkpoint-2000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dc5fa3ab2e76e63a76d96d1e2420300bea66d7082b0e604c6c4f6b71e904105a
3
+ size 1465
checkpoint-2000/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-2000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
3
+ size 500058
checkpoint-2000/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": true,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false,
43
+ "use_fast": true
44
+ }
checkpoint-2000/trainer_state.json ADDED
@@ -0,0 +1,1110 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.5003750937734432,
6
+ "eval_steps": 1000,
7
+ "global_step": 2000,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0,
14
+ "eval_loss": 1.6887853145599365,
15
+ "eval_ppl": 5.4129,
16
+ "eval_runtime": 167.3526,
17
+ "eval_samples_per_second": 4.362,
18
+ "eval_steps_per_second": 0.872,
19
+ "memory/device_reserved (GiB)": 139.12,
20
+ "memory/max_active (GiB)": 18.94,
21
+ "memory/max_allocated (GiB)": 18.94,
22
+ "step": 0
23
+ },
24
+ {
25
+ "epoch": 0.018754688672168042,
26
+ "grad_norm": 1.415561556816101,
27
+ "learning_rate": 4.8e-05,
28
+ "loss": 1.6848,
29
+ "memory/device_reserved (GiB)": 139.11,
30
+ "memory/max_active (GiB)": 25.53,
31
+ "memory/max_allocated (GiB)": 25.53,
32
+ "ppl": 5.3914,
33
+ "step": 25,
34
+ "tokens_per_second_per_gpu": 16277.76,
35
+ "total_tokens": 1723633
36
+ },
37
+ {
38
+ "epoch": 0.037509377344336084,
39
+ "grad_norm": 0.33179354667663574,
40
+ "learning_rate": 9.8e-05,
41
+ "loss": 0.9839,
42
+ "memory/device_reserved (GiB)": 139.06,
43
+ "memory/max_active (GiB)": 25.53,
44
+ "memory/max_allocated (GiB)": 25.53,
45
+ "ppl": 2.6749,
46
+ "step": 50,
47
+ "tokens_per_second_per_gpu": 4303.21,
48
+ "total_tokens": 2175386
49
+ },
50
+ {
51
+ "epoch": 0.056264066016504126,
52
+ "grad_norm": 0.17453454434871674,
53
+ "learning_rate": 0.000148,
54
+ "loss": 0.8002,
55
+ "memory/device_reserved (GiB)": 139.06,
56
+ "memory/max_active (GiB)": 25.53,
57
+ "memory/max_allocated (GiB)": 25.53,
58
+ "ppl": 2.226,
59
+ "step": 75,
60
+ "tokens_per_second_per_gpu": 3776.03,
61
+ "total_tokens": 2623712
62
+ },
63
+ {
64
+ "epoch": 0.07501875468867217,
65
+ "grad_norm": 0.19318008422851562,
66
+ "learning_rate": 0.00019800000000000002,
67
+ "loss": 0.7218,
68
+ "memory/device_reserved (GiB)": 139.06,
69
+ "memory/max_active (GiB)": 25.53,
70
+ "memory/max_allocated (GiB)": 25.53,
71
+ "ppl": 2.0581,
72
+ "step": 100,
73
+ "tokens_per_second_per_gpu": 4252.49,
74
+ "total_tokens": 3072519
75
+ },
76
+ {
77
+ "epoch": 0.09377344336084022,
78
+ "grad_norm": 0.18435686826705933,
79
+ "learning_rate": 0.00019998127418269004,
80
+ "loss": 0.6759,
81
+ "memory/device_reserved (GiB)": 139.06,
82
+ "memory/max_active (GiB)": 25.53,
83
+ "memory/max_allocated (GiB)": 25.53,
84
+ "ppl": 1.9658,
85
+ "step": 125,
86
+ "tokens_per_second_per_gpu": 4303.31,
87
+ "total_tokens": 3523983
88
+ },
89
+ {
90
+ "epoch": 0.11252813203300825,
91
+ "grad_norm": 0.19870473444461823,
92
+ "learning_rate": 0.00019992195096972548,
93
+ "loss": 0.6703,
94
+ "memory/device_reserved (GiB)": 139.06,
95
+ "memory/max_active (GiB)": 25.53,
96
+ "memory/max_allocated (GiB)": 25.53,
97
+ "ppl": 1.9548,
98
+ "step": 150,
99
+ "tokens_per_second_per_gpu": 4260.86,
100
+ "total_tokens": 3973452
101
+ },
102
+ {
103
+ "epoch": 0.1312828207051763,
104
+ "grad_norm": 0.20499658584594727,
105
+ "learning_rate": 0.0001998220219574743,
106
+ "loss": 0.6381,
107
+ "memory/device_reserved (GiB)": 139.06,
108
+ "memory/max_active (GiB)": 25.53,
109
+ "memory/max_allocated (GiB)": 25.53,
110
+ "ppl": 1.8929,
111
+ "step": 175,
112
+ "tokens_per_second_per_gpu": 4288.64,
113
+ "total_tokens": 4423763
114
+ },
115
+ {
116
+ "epoch": 0.15003750937734434,
117
+ "grad_norm": 0.18934418261051178,
118
+ "learning_rate": 0.00019968152775460537,
119
+ "loss": 0.6383,
120
+ "memory/device_reserved (GiB)": 139.06,
121
+ "memory/max_active (GiB)": 25.53,
122
+ "memory/max_allocated (GiB)": 25.53,
123
+ "ppl": 1.8933,
124
+ "step": 200,
125
+ "tokens_per_second_per_gpu": 4244.79,
126
+ "total_tokens": 4872365
127
+ },
128
+ {
129
+ "epoch": 0.16879219804951237,
130
+ "grad_norm": 0.1827855408191681,
131
+ "learning_rate": 0.00019950052545447352,
132
+ "loss": 0.6347,
133
+ "memory/device_reserved (GiB)": 139.06,
134
+ "memory/max_active (GiB)": 25.53,
135
+ "memory/max_allocated (GiB)": 25.53,
136
+ "ppl": 1.8865,
137
+ "step": 225,
138
+ "tokens_per_second_per_gpu": 4252.71,
139
+ "total_tokens": 5319322
140
+ },
141
+ {
142
+ "epoch": 0.18754688672168043,
143
+ "grad_norm": 0.16483066976070404,
144
+ "learning_rate": 0.00019927908861191827,
145
+ "loss": 0.6392,
146
+ "memory/device_reserved (GiB)": 139.06,
147
+ "memory/max_active (GiB)": 25.53,
148
+ "memory/max_allocated (GiB)": 25.53,
149
+ "ppl": 1.895,
150
+ "step": 250,
151
+ "tokens_per_second_per_gpu": 3772.0,
152
+ "total_tokens": 5768644
153
+ },
154
+ {
155
+ "epoch": 0.20630157539384847,
156
+ "grad_norm": 0.17186357080936432,
157
+ "learning_rate": 0.00019901730721337302,
158
+ "loss": 0.614,
159
+ "memory/device_reserved (GiB)": 139.06,
160
+ "memory/max_active (GiB)": 25.53,
161
+ "memory/max_allocated (GiB)": 25.53,
162
+ "ppl": 1.8478,
163
+ "step": 275,
164
+ "tokens_per_second_per_gpu": 4281.82,
165
+ "total_tokens": 6220751
166
+ },
167
+ {
168
+ "epoch": 0.2250562640660165,
169
+ "grad_norm": 0.18073013424873352,
170
+ "learning_rate": 0.00019871528764029667,
171
+ "loss": 0.6196,
172
+ "memory/device_reserved (GiB)": 139.06,
173
+ "memory/max_active (GiB)": 25.53,
174
+ "memory/max_allocated (GiB)": 25.53,
175
+ "ppl": 1.8582,
176
+ "step": 300,
177
+ "tokens_per_second_per_gpu": 4234.51,
178
+ "total_tokens": 6668111
179
+ },
180
+ {
181
+ "epoch": 0.24381095273818454,
182
+ "grad_norm": 0.19639697670936584,
183
+ "learning_rate": 0.00019837315262594306,
184
+ "loss": 0.6181,
185
+ "memory/device_reserved (GiB)": 139.06,
186
+ "memory/max_active (GiB)": 25.53,
187
+ "memory/max_allocated (GiB)": 25.53,
188
+ "ppl": 1.8554,
189
+ "step": 325,
190
+ "tokens_per_second_per_gpu": 4261.44,
191
+ "total_tokens": 7117439
192
+ },
193
+ {
194
+ "epoch": 0.2625656414103526,
195
+ "grad_norm": 0.1670486479997635,
196
+ "learning_rate": 0.00019799104120548492,
197
+ "loss": 0.6141,
198
+ "memory/device_reserved (GiB)": 139.06,
199
+ "memory/max_active (GiB)": 25.53,
200
+ "memory/max_allocated (GiB)": 25.53,
201
+ "ppl": 1.848,
202
+ "step": 350,
203
+ "tokens_per_second_per_gpu": 4298.97,
204
+ "total_tokens": 7569060
205
+ },
206
+ {
207
+ "epoch": 0.2813203300825206,
208
+ "grad_norm": 0.17752495408058167,
209
+ "learning_rate": 0.00019756910865951377,
210
+ "loss": 0.6075,
211
+ "memory/device_reserved (GiB)": 139.06,
212
+ "memory/max_active (GiB)": 25.53,
213
+ "memory/max_allocated (GiB)": 25.53,
214
+ "ppl": 1.8358,
215
+ "step": 375,
216
+ "tokens_per_second_per_gpu": 4256.6,
217
+ "total_tokens": 8017630
218
+ },
219
+ {
220
+ "epoch": 0.30007501875468867,
221
+ "grad_norm": 0.2000180035829544,
222
+ "learning_rate": 0.00019710752645093747,
223
+ "loss": 0.6108,
224
+ "memory/device_reserved (GiB)": 139.06,
225
+ "memory/max_active (GiB)": 25.53,
226
+ "memory/max_allocated (GiB)": 25.53,
227
+ "ppl": 1.8419,
228
+ "step": 400,
229
+ "tokens_per_second_per_gpu": 4245.46,
230
+ "total_tokens": 8464998
231
+ },
232
+ {
233
+ "epoch": 0.31882970742685673,
234
+ "grad_norm": 0.17395919561386108,
235
+ "learning_rate": 0.00019660648215530206,
236
+ "loss": 0.5966,
237
+ "memory/device_reserved (GiB)": 139.06,
238
+ "memory/max_active (GiB)": 25.53,
239
+ "memory/max_allocated (GiB)": 25.53,
240
+ "ppl": 1.8159,
241
+ "step": 425,
242
+ "tokens_per_second_per_gpu": 3758.92,
243
+ "total_tokens": 8914723
244
+ },
245
+ {
246
+ "epoch": 0.33758439609902474,
247
+ "grad_norm": 0.18785236775875092,
248
+ "learning_rate": 0.00019606617938456572,
249
+ "loss": 0.6099,
250
+ "memory/device_reserved (GiB)": 139.06,
251
+ "memory/max_active (GiB)": 25.53,
252
+ "memory/max_allocated (GiB)": 25.53,
253
+ "ppl": 1.8402,
254
+ "step": 450,
255
+ "tokens_per_second_per_gpu": 4200.53,
256
+ "total_tokens": 9359638
257
+ },
258
+ {
259
+ "epoch": 0.3563390847711928,
260
+ "grad_norm": 0.17702797055244446,
261
+ "learning_rate": 0.0001954868377043559,
262
+ "loss": 0.5922,
263
+ "memory/device_reserved (GiB)": 139.06,
264
+ "memory/max_active (GiB)": 25.53,
265
+ "memory/max_allocated (GiB)": 25.53,
266
+ "ppl": 1.808,
267
+ "step": 475,
268
+ "tokens_per_second_per_gpu": 4265.36,
269
+ "total_tokens": 9810837
270
+ },
271
+ {
272
+ "epoch": 0.37509377344336087,
273
+ "grad_norm": 0.19927558302879333,
274
+ "learning_rate": 0.00019486869254474337,
275
+ "loss": 0.5759,
276
+ "memory/device_reserved (GiB)": 139.06,
277
+ "memory/max_active (GiB)": 25.53,
278
+ "memory/max_allocated (GiB)": 25.53,
279
+ "ppl": 1.7787,
280
+ "step": 500,
281
+ "tokens_per_second_per_gpu": 4276.25,
282
+ "total_tokens": 10261446
283
+ },
284
+ {
285
+ "epoch": 0.3938484621155289,
286
+ "grad_norm": 0.1908370852470398,
287
+ "learning_rate": 0.0001942119951045692,
288
+ "loss": 0.584,
289
+ "memory/device_reserved (GiB)": 139.06,
290
+ "memory/max_active (GiB)": 25.53,
291
+ "memory/max_allocated (GiB)": 25.53,
292
+ "ppl": 1.7932,
293
+ "step": 525,
294
+ "tokens_per_second_per_gpu": 4272.28,
295
+ "total_tokens": 10707841
296
+ },
297
+ {
298
+ "epoch": 0.41260315078769694,
299
+ "grad_norm": 0.2064146101474762,
300
+ "learning_rate": 0.00019351701224936383,
301
+ "loss": 0.5791,
302
+ "memory/device_reserved (GiB)": 139.06,
303
+ "memory/max_active (GiB)": 25.53,
304
+ "memory/max_allocated (GiB)": 25.53,
305
+ "ppl": 1.7844,
306
+ "step": 550,
307
+ "tokens_per_second_per_gpu": 4250.37,
308
+ "total_tokens": 11155384
309
+ },
310
+ {
311
+ "epoch": 0.43135783945986494,
312
+ "grad_norm": 0.26748332381248474,
313
+ "learning_rate": 0.0001927840264028995,
314
+ "loss": 0.5758,
315
+ "memory/device_reserved (GiB)": 139.06,
316
+ "memory/max_active (GiB)": 25.53,
317
+ "memory/max_allocated (GiB)": 25.53,
318
+ "ppl": 1.7786,
319
+ "step": 575,
320
+ "tokens_per_second_per_gpu": 4256.55,
321
+ "total_tokens": 11601192
322
+ },
323
+ {
324
+ "epoch": 0.450112528132033,
325
+ "grad_norm": 0.17514832317829132,
326
+ "learning_rate": 0.00019201333543242036,
327
+ "loss": 0.5791,
328
+ "memory/device_reserved (GiB)": 139.06,
329
+ "memory/max_active (GiB)": 25.53,
330
+ "memory/max_allocated (GiB)": 25.53,
331
+ "ppl": 1.7844,
332
+ "step": 600,
333
+ "tokens_per_second_per_gpu": 3770.83,
334
+ "total_tokens": 12048477
335
+ },
336
+ {
337
+ "epoch": 0.46886721680420107,
338
+ "grad_norm": 0.22069169580936432,
339
+ "learning_rate": 0.00019120525252759647,
340
+ "loss": 0.5803,
341
+ "memory/device_reserved (GiB)": 139.06,
342
+ "memory/max_active (GiB)": 25.53,
343
+ "memory/max_allocated (GiB)": 25.53,
344
+ "ppl": 1.7866,
345
+ "step": 625,
346
+ "tokens_per_second_per_gpu": 4179.31,
347
+ "total_tokens": 12488141
348
+ },
349
+ {
350
+ "epoch": 0.4876219054763691,
351
+ "grad_norm": 0.20555566251277924,
352
+ "learning_rate": 0.00019036010607325138,
353
+ "loss": 0.5716,
354
+ "memory/device_reserved (GiB)": 139.06,
355
+ "memory/max_active (GiB)": 25.53,
356
+ "memory/max_allocated (GiB)": 25.53,
357
+ "ppl": 1.7711,
358
+ "step": 650,
359
+ "tokens_per_second_per_gpu": 4209.96,
360
+ "total_tokens": 12934358
361
+ },
362
+ {
363
+ "epoch": 0.5063765941485371,
364
+ "grad_norm": 0.19018156826496124,
365
+ "learning_rate": 0.00018947823951591478,
366
+ "loss": 0.5608,
367
+ "memory/device_reserved (GiB)": 139.06,
368
+ "memory/max_active (GiB)": 25.53,
369
+ "memory/max_allocated (GiB)": 25.53,
370
+ "ppl": 1.7521,
371
+ "step": 675,
372
+ "tokens_per_second_per_gpu": 4226.4,
373
+ "total_tokens": 13378983
374
+ },
375
+ {
376
+ "epoch": 0.5251312828207052,
377
+ "grad_norm": 0.17173859477043152,
378
+ "learning_rate": 0.00018856001122425416,
379
+ "loss": 0.5667,
380
+ "memory/device_reserved (GiB)": 139.06,
381
+ "memory/max_active (GiB)": 25.53,
382
+ "memory/max_allocated (GiB)": 25.53,
383
+ "ppl": 1.7624,
384
+ "step": 700,
385
+ "tokens_per_second_per_gpu": 4265.57,
386
+ "total_tokens": 13829519
387
+ },
388
+ {
389
+ "epoch": 0.5438859714928732,
390
+ "grad_norm": 0.17706550657749176,
391
+ "learning_rate": 0.0001876057943434428,
392
+ "loss": 0.565,
393
+ "memory/device_reserved (GiB)": 139.06,
394
+ "memory/max_active (GiB)": 25.53,
395
+ "memory/max_allocated (GiB)": 25.53,
396
+ "ppl": 1.7594,
397
+ "step": 725,
398
+ "tokens_per_second_per_gpu": 4281.61,
399
+ "total_tokens": 14281879
400
+ },
401
+ {
402
+ "epoch": 0.5626406601650412,
403
+ "grad_norm": 0.18528586626052856,
404
+ "learning_rate": 0.00018661597664352284,
405
+ "loss": 0.5666,
406
+ "memory/device_reserved (GiB)": 139.06,
407
+ "memory/max_active (GiB)": 25.53,
408
+ "memory/max_allocated (GiB)": 25.53,
409
+ "ppl": 1.7623,
410
+ "step": 750,
411
+ "tokens_per_second_per_gpu": 4229.32,
412
+ "total_tokens": 14725919
413
+ },
414
+ {
415
+ "epoch": 0.5813953488372093,
416
+ "grad_norm": 0.16790929436683655,
417
+ "learning_rate": 0.00018559096036182516,
418
+ "loss": 0.5633,
419
+ "memory/device_reserved (GiB)": 139.06,
420
+ "memory/max_active (GiB)": 25.53,
421
+ "memory/max_allocated (GiB)": 25.53,
422
+ "ppl": 1.7565,
423
+ "step": 775,
424
+ "tokens_per_second_per_gpu": 3775.0,
425
+ "total_tokens": 15175146
426
+ },
427
+ {
428
+ "epoch": 0.6001500375093773,
429
+ "grad_norm": 0.17511805891990662,
430
+ "learning_rate": 0.00018453116203951005,
431
+ "loss": 0.5664,
432
+ "memory/device_reserved (GiB)": 139.06,
433
+ "memory/max_active (GiB)": 25.53,
434
+ "memory/max_allocated (GiB)": 25.53,
435
+ "ppl": 1.7619,
436
+ "step": 800,
437
+ "tokens_per_second_per_gpu": 4218.07,
438
+ "total_tokens": 15619901
439
+ },
440
+ {
441
+ "epoch": 0.6189047261815454,
442
+ "grad_norm": 0.19853387773036957,
443
+ "learning_rate": 0.0001834370123522954,
444
+ "loss": 0.5646,
445
+ "memory/device_reserved (GiB)": 139.06,
446
+ "memory/max_active (GiB)": 25.53,
447
+ "memory/max_allocated (GiB)": 25.53,
448
+ "ppl": 1.7587,
449
+ "step": 825,
450
+ "tokens_per_second_per_gpu": 4230.84,
451
+ "total_tokens": 16066102
452
+ },
453
+ {
454
+ "epoch": 0.6376594148537135,
455
+ "grad_norm": 0.18872258067131042,
456
+ "learning_rate": 0.00018230895593544056,
457
+ "loss": 0.552,
458
+ "memory/device_reserved (GiB)": 139.06,
459
+ "memory/max_active (GiB)": 25.53,
460
+ "memory/max_allocated (GiB)": 25.53,
461
+ "ppl": 1.7367,
462
+ "step": 850,
463
+ "tokens_per_second_per_gpu": 4222.33,
464
+ "total_tokens": 16510696
465
+ },
466
+ {
467
+ "epoch": 0.6564141035258815,
468
+ "grad_norm": 0.9702818989753723,
469
+ "learning_rate": 0.0001811474512030578,
470
+ "loss": 0.5607,
471
+ "memory/device_reserved (GiB)": 139.06,
472
+ "memory/max_active (GiB)": 25.53,
473
+ "memory/max_allocated (GiB)": 25.53,
474
+ "ppl": 1.7519,
475
+ "step": 875,
476
+ "tokens_per_second_per_gpu": 4200.39,
477
+ "total_tokens": 16953918
478
+ },
479
+ {
480
+ "epoch": 0.6751687921980495,
481
+ "grad_norm": 0.17479568719863892,
482
+ "learning_rate": 0.00017995297016182405,
483
+ "loss": 0.564,
484
+ "memory/device_reserved (GiB)": 139.06,
485
+ "memory/max_active (GiB)": 25.53,
486
+ "memory/max_allocated (GiB)": 25.53,
487
+ "ppl": 1.7577,
488
+ "step": 900,
489
+ "tokens_per_second_per_gpu": 4210.15,
490
+ "total_tokens": 17396453
491
+ },
492
+ {
493
+ "epoch": 0.6939234808702176,
494
+ "grad_norm": 0.1948954463005066,
495
+ "learning_rate": 0.0001787259982191692,
496
+ "loss": 0.5511,
497
+ "memory/device_reserved (GiB)": 139.06,
498
+ "memory/max_active (GiB)": 25.53,
499
+ "memory/max_allocated (GiB)": 25.53,
500
+ "ppl": 1.7352,
501
+ "step": 925,
502
+ "tokens_per_second_per_gpu": 4237.98,
503
+ "total_tokens": 17841287
504
+ },
505
+ {
506
+ "epoch": 0.7126781695423856,
507
+ "grad_norm": 0.19541053473949432,
508
+ "learning_rate": 0.00017746703398601872,
509
+ "loss": 0.5532,
510
+ "memory/device_reserved (GiB)": 139.06,
511
+ "memory/max_active (GiB)": 25.53,
512
+ "memory/max_allocated (GiB)": 25.53,
513
+ "ppl": 1.7388,
514
+ "step": 950,
515
+ "tokens_per_second_per_gpu": 3725.33,
516
+ "total_tokens": 18283596
517
+ },
518
+ {
519
+ "epoch": 0.7314328582145536,
520
+ "grad_norm": 0.1818365603685379,
521
+ "learning_rate": 0.0001761765890741701,
522
+ "loss": 0.5521,
523
+ "memory/device_reserved (GiB)": 139.06,
524
+ "memory/max_active (GiB)": 25.53,
525
+ "memory/max_allocated (GiB)": 25.53,
526
+ "ppl": 1.7369,
527
+ "step": 975,
528
+ "tokens_per_second_per_gpu": 4211.63,
529
+ "total_tokens": 18726722
530
+ },
531
+ {
532
+ "epoch": 0.7501875468867217,
533
+ "grad_norm": 0.1838025599718094,
534
+ "learning_rate": 0.00017485518788838705,
535
+ "loss": 0.5511,
536
+ "memory/device_reserved (GiB)": 139.06,
537
+ "memory/max_active (GiB)": 25.53,
538
+ "memory/max_allocated (GiB)": 25.53,
539
+ "ppl": 1.7352,
540
+ "step": 1000,
541
+ "tokens_per_second_per_gpu": 3962.4,
542
+ "total_tokens": 19167258
543
+ },
544
+ {
545
+ "epoch": 0.7501875468867217,
546
+ "eval_loss": 0.540988564491272,
547
+ "eval_ppl": 1.7177,
548
+ "eval_runtime": 138.0264,
549
+ "eval_samples_per_second": 5.289,
550
+ "eval_steps_per_second": 1.058,
551
+ "memory/device_reserved (GiB)": 139.02,
552
+ "memory/max_active (GiB)": 19.1,
553
+ "memory/max_allocated (GiB)": 19.1,
554
+ "step": 1000
555
+ },
556
+ {
557
+ "epoch": 0.7689422355588897,
558
+ "grad_norm": 0.2199818342924118,
559
+ "learning_rate": 0.00017350336741329413,
560
+ "loss": 0.549,
561
+ "memory/device_reserved (GiB)": 139.06,
562
+ "memory/max_active (GiB)": 25.53,
563
+ "memory/max_allocated (GiB)": 25.53,
564
+ "ppl": 1.7315,
565
+ "step": 1025,
566
+ "tokens_per_second_per_gpu": 4129.73,
567
+ "total_tokens": 20870820
568
+ },
569
+ {
570
+ "epoch": 0.7876969242310577,
571
+ "grad_norm": 0.19783177971839905,
572
+ "learning_rate": 0.0001721216769951596,
573
+ "loss": 0.5615,
574
+ "memory/device_reserved (GiB)": 139.06,
575
+ "memory/max_active (GiB)": 25.53,
576
+ "memory/max_allocated (GiB)": 25.53,
577
+ "ppl": 1.7533,
578
+ "step": 1050,
579
+ "tokens_per_second_per_gpu": 4243.63,
580
+ "total_tokens": 21317982
581
+ },
582
+ {
583
+ "epoch": 0.8064516129032258,
584
+ "grad_norm": 0.1678430140018463,
585
+ "learning_rate": 0.00017071067811865476,
586
+ "loss": 0.5557,
587
+ "memory/device_reserved (GiB)": 139.06,
588
+ "memory/max_active (GiB)": 25.53,
589
+ "memory/max_allocated (GiB)": 25.53,
590
+ "ppl": 1.7432,
591
+ "step": 1075,
592
+ "tokens_per_second_per_gpu": 4092.04,
593
+ "total_tokens": 21754087
594
+ },
595
+ {
596
+ "epoch": 0.8252063015753939,
597
+ "grad_norm": 0.16523879766464233,
598
+ "learning_rate": 0.00016927094417868048,
599
+ "loss": 0.556,
600
+ "memory/device_reserved (GiB)": 139.06,
601
+ "memory/max_active (GiB)": 25.53,
602
+ "memory/max_allocated (GiB)": 25.53,
603
+ "ppl": 1.7437,
604
+ "step": 1100,
605
+ "tokens_per_second_per_gpu": 4187.02,
606
+ "total_tokens": 22198779
607
+ },
608
+ {
609
+ "epoch": 0.8439609902475619,
610
+ "grad_norm": 0.18177717924118042,
611
+ "learning_rate": 0.00016780306024735382,
612
+ "loss": 0.5468,
613
+ "memory/device_reserved (GiB)": 139.06,
614
+ "memory/max_active (GiB)": 25.53,
615
+ "memory/max_allocated (GiB)": 25.53,
616
+ "ppl": 1.7277,
617
+ "step": 1125,
618
+ "tokens_per_second_per_gpu": 4198.97,
619
+ "total_tokens": 22639769
620
+ },
621
+ {
622
+ "epoch": 0.8627156789197299,
623
+ "grad_norm": 0.17299720644950867,
624
+ "learning_rate": 0.0001663076228362492,
625
+ "loss": 0.554,
626
+ "memory/device_reserved (GiB)": 139.06,
627
+ "memory/max_active (GiB)": 25.53,
628
+ "memory/max_allocated (GiB)": 25.53,
629
+ "ppl": 1.7402,
630
+ "step": 1150,
631
+ "tokens_per_second_per_gpu": 3762.13,
632
+ "total_tokens": 23086742
633
+ },
634
+ {
635
+ "epoch": 0.881470367591898,
636
+ "grad_norm": 0.19112971425056458,
637
+ "learning_rate": 0.00016478523965399085,
638
+ "loss": 0.5434,
639
+ "memory/device_reserved (GiB)": 139.06,
640
+ "memory/max_active (GiB)": 25.53,
641
+ "memory/max_allocated (GiB)": 25.53,
642
+ "ppl": 1.7219,
643
+ "step": 1175,
644
+ "tokens_per_second_per_gpu": 4205.37,
645
+ "total_tokens": 23528106
646
+ },
647
+ {
648
+ "epoch": 0.900225056264066,
649
+ "grad_norm": 0.17930163443088531,
650
+ "learning_rate": 0.00016323652935929536,
651
+ "loss": 0.5362,
652
+ "memory/device_reserved (GiB)": 139.06,
653
+ "memory/max_active (GiB)": 25.53,
654
+ "memory/max_allocated (GiB)": 25.53,
655
+ "ppl": 1.7095,
656
+ "step": 1200,
657
+ "tokens_per_second_per_gpu": 4228.83,
658
+ "total_tokens": 23974427
659
+ },
660
+ {
661
+ "epoch": 0.918979744936234,
662
+ "grad_norm": 0.18718039989471436,
663
+ "learning_rate": 0.00016166212130956382,
664
+ "loss": 0.5533,
665
+ "memory/device_reserved (GiB)": 139.06,
666
+ "memory/max_active (GiB)": 25.53,
667
+ "memory/max_allocated (GiB)": 25.53,
668
+ "ppl": 1.739,
669
+ "step": 1225,
670
+ "tokens_per_second_per_gpu": 4211.64,
671
+ "total_tokens": 24415919
672
+ },
673
+ {
674
+ "epoch": 0.9377344336084021,
675
+ "grad_norm": 0.17105573415756226,
676
+ "learning_rate": 0.0001600626553051268,
677
+ "loss": 0.5492,
678
+ "memory/device_reserved (GiB)": 139.06,
679
+ "memory/max_active (GiB)": 25.53,
680
+ "memory/max_allocated (GiB)": 25.53,
681
+ "ppl": 1.7319,
682
+ "step": 1250,
683
+ "tokens_per_second_per_gpu": 4183.86,
684
+ "total_tokens": 24854345
685
+ },
686
+ {
687
+ "epoch": 0.9564891222805701,
688
+ "grad_norm": 0.1733955442905426,
689
+ "learning_rate": 0.0001584387813292454,
690
+ "loss": 0.5348,
691
+ "memory/device_reserved (GiB)": 139.06,
692
+ "memory/max_active (GiB)": 25.53,
693
+ "memory/max_allocated (GiB)": 25.53,
694
+ "ppl": 1.7071,
695
+ "step": 1275,
696
+ "tokens_per_second_per_gpu": 4172.93,
697
+ "total_tokens": 25292647
698
+ },
699
+ {
700
+ "epoch": 0.9752438109527382,
701
+ "grad_norm": 0.1858205944299698,
702
+ "learning_rate": 0.00015679115928397401,
703
+ "loss": 0.5527,
704
+ "memory/device_reserved (GiB)": 139.06,
705
+ "memory/max_active (GiB)": 25.53,
706
+ "memory/max_allocated (GiB)": 25.53,
707
+ "ppl": 1.7379,
708
+ "step": 1300,
709
+ "tokens_per_second_per_gpu": 4226.34,
710
+ "total_tokens": 25733591
711
+ },
712
+ {
713
+ "epoch": 0.9939984996249063,
714
+ "grad_norm": 0.1944192498922348,
715
+ "learning_rate": 0.00015512045872199276,
716
+ "loss": 0.5311,
717
+ "memory/device_reserved (GiB)": 139.06,
718
+ "memory/max_active (GiB)": 25.53,
719
+ "memory/max_allocated (GiB)": 25.53,
720
+ "ppl": 1.7008,
721
+ "step": 1325,
722
+ "tokens_per_second_per_gpu": 3655.12,
723
+ "total_tokens": 26164528
724
+ },
725
+ {
726
+ "epoch": 1.0127531882970742,
727
+ "grad_norm": 0.18358173966407776,
728
+ "learning_rate": 0.00015342735857451777,
729
+ "loss": 0.5145,
730
+ "memory/device_reserved (GiB)": 139.06,
731
+ "memory/max_active (GiB)": 25.53,
732
+ "memory/max_allocated (GiB)": 25.53,
733
+ "ppl": 1.6728,
734
+ "step": 1350,
735
+ "tokens_per_second_per_gpu": 4227.25,
736
+ "total_tokens": 26610460
737
+ },
738
+ {
739
+ "epoch": 1.0315078769692423,
740
+ "grad_norm": 0.1853465735912323,
741
+ "learning_rate": 0.00015171254687540038,
742
+ "loss": 0.5081,
743
+ "memory/device_reserved (GiB)": 139.06,
744
+ "memory/max_active (GiB)": 25.53,
745
+ "memory/max_allocated (GiB)": 25.53,
746
+ "ppl": 1.6621,
747
+ "step": 1375,
748
+ "tokens_per_second_per_gpu": 4318.88,
749
+ "total_tokens": 27064008
750
+ },
751
+ {
752
+ "epoch": 1.0502625656414104,
753
+ "grad_norm": 0.18925060331821442,
754
+ "learning_rate": 0.0001499767204815273,
755
+ "loss": 0.5185,
756
+ "memory/device_reserved (GiB)": 139.06,
757
+ "memory/max_active (GiB)": 25.53,
758
+ "memory/max_allocated (GiB)": 25.53,
759
+ "ppl": 1.6795,
760
+ "step": 1400,
761
+ "tokens_per_second_per_gpu": 4324.01,
762
+ "total_tokens": 27516590
763
+ },
764
+ {
765
+ "epoch": 1.0690172543135783,
766
+ "grad_norm": 0.20961470901966095,
767
+ "learning_rate": 0.00014822058478963532,
768
+ "loss": 0.5234,
769
+ "memory/device_reserved (GiB)": 139.06,
770
+ "memory/max_active (GiB)": 25.53,
771
+ "memory/max_allocated (GiB)": 25.53,
772
+ "ppl": 1.6878,
773
+ "step": 1425,
774
+ "tokens_per_second_per_gpu": 4319.64,
775
+ "total_tokens": 27970075
776
+ },
777
+ {
778
+ "epoch": 1.0877719429857464,
779
+ "grad_norm": 0.1982697695493698,
780
+ "learning_rate": 0.0001464448534496555,
781
+ "loss": 0.5169,
782
+ "memory/device_reserved (GiB)": 139.06,
783
+ "memory/max_active (GiB)": 25.53,
784
+ "memory/max_allocated (GiB)": 25.53,
785
+ "ppl": 1.6768,
786
+ "step": 1450,
787
+ "tokens_per_second_per_gpu": 4267.88,
788
+ "total_tokens": 28419716
789
+ },
790
+ {
791
+ "epoch": 1.1065266316579145,
792
+ "grad_norm": 0.1925143301486969,
793
+ "learning_rate": 0.00014465024807470376,
794
+ "loss": 0.5197,
795
+ "memory/device_reserved (GiB)": 139.06,
796
+ "memory/max_active (GiB)": 25.53,
797
+ "memory/max_allocated (GiB)": 25.53,
798
+ "ppl": 1.6815,
799
+ "step": 1475,
800
+ "tokens_per_second_per_gpu": 4264.53,
801
+ "total_tokens": 28866312
802
+ },
803
+ {
804
+ "epoch": 1.1252813203300824,
805
+ "grad_norm": 0.18788637220859528,
806
+ "learning_rate": 0.0001428374979478349,
807
+ "loss": 0.5204,
808
+ "memory/device_reserved (GiB)": 139.06,
809
+ "memory/max_active (GiB)": 25.53,
810
+ "memory/max_allocated (GiB)": 25.53,
811
+ "ppl": 1.6827,
812
+ "step": 1500,
813
+ "tokens_per_second_per_gpu": 3779.33,
814
+ "total_tokens": 29315968
815
+ },
816
+ {
817
+ "epoch": 1.1440360090022506,
818
+ "grad_norm": 0.18954145908355713,
819
+ "learning_rate": 0.00014100733972568038,
820
+ "loss": 0.5164,
821
+ "memory/device_reserved (GiB)": 139.06,
822
+ "memory/max_active (GiB)": 25.53,
823
+ "memory/max_allocated (GiB)": 25.53,
824
+ "ppl": 1.676,
825
+ "step": 1525,
826
+ "tokens_per_second_per_gpu": 4282.57,
827
+ "total_tokens": 29766723
828
+ },
829
+ {
830
+ "epoch": 1.1627906976744187,
831
+ "grad_norm": 0.19003146886825562,
832
+ "learning_rate": 0.00013916051713908924,
833
+ "loss": 0.5095,
834
+ "memory/device_reserved (GiB)": 139.06,
835
+ "memory/max_active (GiB)": 25.53,
836
+ "memory/max_allocated (GiB)": 25.53,
837
+ "ppl": 1.6645,
838
+ "step": 1550,
839
+ "tokens_per_second_per_gpu": 4290.76,
840
+ "total_tokens": 30218573
841
+ },
842
+ {
843
+ "epoch": 1.1815453863465866,
844
+ "grad_norm": 0.18279583752155304,
845
+ "learning_rate": 0.00013729778069089437,
846
+ "loss": 0.522,
847
+ "memory/device_reserved (GiB)": 139.06,
848
+ "memory/max_active (GiB)": 25.53,
849
+ "memory/max_allocated (GiB)": 25.53,
850
+ "ppl": 1.6854,
851
+ "step": 1575,
852
+ "tokens_per_second_per_gpu": 4300.13,
853
+ "total_tokens": 30669810
854
+ },
855
+ {
856
+ "epoch": 1.2003000750187547,
857
+ "grad_norm": 0.18783092498779297,
858
+ "learning_rate": 0.00013541988735092672,
859
+ "loss": 0.5003,
860
+ "memory/device_reserved (GiB)": 139.06,
861
+ "memory/max_active (GiB)": 25.53,
862
+ "memory/max_allocated (GiB)": 25.53,
863
+ "ppl": 1.6492,
864
+ "step": 1600,
865
+ "tokens_per_second_per_gpu": 4271.27,
866
+ "total_tokens": 31117586
867
+ },
868
+ {
869
+ "epoch": 1.2190547636909228,
870
+ "grad_norm": 0.199558824300766,
871
+ "learning_rate": 0.00013352760024840175,
872
+ "loss": 0.5115,
873
+ "memory/device_reserved (GiB)": 139.06,
874
+ "memory/max_active (GiB)": 25.53,
875
+ "memory/max_allocated (GiB)": 25.53,
876
+ "ppl": 1.6678,
877
+ "step": 1625,
878
+ "tokens_per_second_per_gpu": 4248.14,
879
+ "total_tokens": 31562224
880
+ },
881
+ {
882
+ "epoch": 1.2378094523630907,
883
+ "grad_norm": 0.19465653598308563,
884
+ "learning_rate": 0.00013162168836180246,
885
+ "loss": 0.4967,
886
+ "memory/device_reserved (GiB)": 139.06,
887
+ "memory/max_active (GiB)": 25.53,
888
+ "memory/max_allocated (GiB)": 25.53,
889
+ "ppl": 1.6433,
890
+ "step": 1650,
891
+ "tokens_per_second_per_gpu": 4286.24,
892
+ "total_tokens": 32011071
893
+ },
894
+ {
895
+ "epoch": 1.2565641410352588,
896
+ "grad_norm": 0.2054641842842102,
897
+ "learning_rate": 0.00012970292620638574,
898
+ "loss": 0.5172,
899
+ "memory/device_reserved (GiB)": 139.06,
900
+ "memory/max_active (GiB)": 25.53,
901
+ "memory/max_allocated (GiB)": 25.53,
902
+ "ppl": 1.6773,
903
+ "step": 1675,
904
+ "tokens_per_second_per_gpu": 3733.1,
905
+ "total_tokens": 32452490
906
+ },
907
+ {
908
+ "epoch": 1.275318829707427,
909
+ "grad_norm": 0.19450411200523376,
910
+ "learning_rate": 0.00012777209351943862,
911
+ "loss": 0.5149,
912
+ "memory/device_reserved (GiB)": 139.06,
913
+ "memory/max_active (GiB)": 25.53,
914
+ "memory/max_allocated (GiB)": 25.53,
915
+ "ppl": 1.6735,
916
+ "step": 1700,
917
+ "tokens_per_second_per_gpu": 4251.33,
918
+ "total_tokens": 32899103
919
+ },
920
+ {
921
+ "epoch": 1.2940735183795948,
922
+ "grad_norm": 0.19844166934490204,
923
+ "learning_rate": 0.0001258299749434123,
924
+ "loss": 0.5205,
925
+ "memory/device_reserved (GiB)": 139.06,
926
+ "memory/max_active (GiB)": 25.53,
927
+ "memory/max_allocated (GiB)": 25.53,
928
+ "ppl": 1.6829,
929
+ "step": 1725,
930
+ "tokens_per_second_per_gpu": 4240.57,
931
+ "total_tokens": 33344569
932
+ },
933
+ {
934
+ "epoch": 1.312828207051763,
935
+ "grad_norm": 0.19240470230579376,
936
+ "learning_rate": 0.00012387735970706312,
937
+ "loss": 0.5033,
938
+ "memory/device_reserved (GiB)": 139.06,
939
+ "memory/max_active (GiB)": 25.53,
940
+ "memory/max_allocated (GiB)": 25.53,
941
+ "ppl": 1.6542,
942
+ "step": 1750,
943
+ "tokens_per_second_per_gpu": 4267.65,
944
+ "total_tokens": 33790426
945
+ },
946
+ {
947
+ "epoch": 1.331582895723931,
948
+ "grad_norm": 0.18220192193984985,
949
+ "learning_rate": 0.00012191504130472937,
950
+ "loss": 0.5103,
951
+ "memory/device_reserved (GiB)": 139.06,
952
+ "memory/max_active (GiB)": 25.53,
953
+ "memory/max_allocated (GiB)": 25.53,
954
+ "ppl": 1.6658,
955
+ "step": 1775,
956
+ "tokens_per_second_per_gpu": 4237.08,
957
+ "total_tokens": 34233908
958
+ },
959
+ {
960
+ "epoch": 1.350337584396099,
961
+ "grad_norm": 0.20157551765441895,
962
+ "learning_rate": 0.00011994381717387514,
963
+ "loss": 0.5192,
964
+ "memory/device_reserved (GiB)": 139.06,
965
+ "memory/max_active (GiB)": 25.53,
966
+ "memory/max_allocated (GiB)": 25.53,
967
+ "ppl": 1.6807,
968
+ "step": 1800,
969
+ "tokens_per_second_per_gpu": 4244.09,
970
+ "total_tokens": 34678691
971
+ },
972
+ {
973
+ "epoch": 1.369092273068267,
974
+ "grad_norm": 0.17189238965511322,
975
+ "learning_rate": 0.00011796448837103129,
976
+ "loss": 0.5011,
977
+ "memory/device_reserved (GiB)": 139.06,
978
+ "memory/max_active (GiB)": 25.53,
979
+ "memory/max_allocated (GiB)": 25.53,
980
+ "ppl": 1.6505,
981
+ "step": 1825,
982
+ "tokens_per_second_per_gpu": 4277.26,
983
+ "total_tokens": 35125624
984
+ },
985
+ {
986
+ "epoch": 1.387846961740435,
987
+ "grad_norm": 0.19443106651306152,
988
+ "learning_rate": 0.00011597785924626616,
989
+ "loss": 0.4994,
990
+ "memory/device_reserved (GiB)": 139.06,
991
+ "memory/max_active (GiB)": 25.53,
992
+ "memory/max_allocated (GiB)": 25.53,
993
+ "ppl": 1.6477,
994
+ "step": 1850,
995
+ "tokens_per_second_per_gpu": 3766.52,
996
+ "total_tokens": 35568850
997
+ },
998
+ {
999
+ "epoch": 1.406601650412603,
1000
+ "grad_norm": 0.1810811311006546,
1001
+ "learning_rate": 0.00011398473711631764,
1002
+ "loss": 0.5083,
1003
+ "memory/device_reserved (GiB)": 139.06,
1004
+ "memory/max_active (GiB)": 25.53,
1005
+ "memory/max_allocated (GiB)": 25.53,
1006
+ "ppl": 1.6625,
1007
+ "step": 1875,
1008
+ "tokens_per_second_per_gpu": 4204.76,
1009
+ "total_tokens": 36009980
1010
+ },
1011
+ {
1012
+ "epoch": 1.4253563390847712,
1013
+ "grad_norm": 0.19805970788002014,
1014
+ "learning_rate": 0.00011198593193651958,
1015
+ "loss": 0.5141,
1016
+ "memory/device_reserved (GiB)": 139.06,
1017
+ "memory/max_active (GiB)": 25.53,
1018
+ "memory/max_allocated (GiB)": 25.53,
1019
+ "ppl": 1.6721,
1020
+ "step": 1900,
1021
+ "tokens_per_second_per_gpu": 4270.21,
1022
+ "total_tokens": 36457032
1023
+ },
1024
+ {
1025
+ "epoch": 1.4441110277569393,
1026
+ "grad_norm": 0.1936168372631073,
1027
+ "learning_rate": 0.00010998225597165628,
1028
+ "loss": 0.5045,
1029
+ "memory/device_reserved (GiB)": 139.06,
1030
+ "memory/max_active (GiB)": 25.53,
1031
+ "memory/max_allocated (GiB)": 25.53,
1032
+ "ppl": 1.6562,
1033
+ "step": 1925,
1034
+ "tokens_per_second_per_gpu": 4275.24,
1035
+ "total_tokens": 36905590
1036
+ },
1037
+ {
1038
+ "epoch": 1.4628657164291072,
1039
+ "grad_norm": 0.19065748155117035,
1040
+ "learning_rate": 0.00010797452346587798,
1041
+ "loss": 0.5025,
1042
+ "memory/device_reserved (GiB)": 139.06,
1043
+ "memory/max_active (GiB)": 25.53,
1044
+ "memory/max_allocated (GiB)": 25.53,
1045
+ "ppl": 1.6528,
1046
+ "step": 1950,
1047
+ "tokens_per_second_per_gpu": 4285.81,
1048
+ "total_tokens": 37354436
1049
+ },
1050
+ {
1051
+ "epoch": 1.4816204051012754,
1052
+ "grad_norm": 0.18647657334804535,
1053
+ "learning_rate": 0.0001059635503118125,
1054
+ "loss": 0.5102,
1055
+ "memory/device_reserved (GiB)": 139.06,
1056
+ "memory/max_active (GiB)": 25.53,
1057
+ "memory/max_allocated (GiB)": 25.53,
1058
+ "ppl": 1.6656,
1059
+ "step": 1975,
1060
+ "tokens_per_second_per_gpu": 4259.76,
1061
+ "total_tokens": 37801500
1062
+ },
1063
+ {
1064
+ "epoch": 1.5003750937734432,
1065
+ "grad_norm": 0.21211788058280945,
1066
+ "learning_rate": 0.00010395015371900663,
1067
+ "loss": 0.5052,
1068
+ "memory/device_reserved (GiB)": 139.06,
1069
+ "memory/max_active (GiB)": 25.53,
1070
+ "memory/max_allocated (GiB)": 25.53,
1071
+ "ppl": 1.6573,
1072
+ "step": 2000,
1073
+ "tokens_per_second_per_gpu": 4250.7,
1074
+ "total_tokens": 38244936
1075
+ },
1076
+ {
1077
+ "epoch": 1.5003750937734432,
1078
+ "eval_loss": 0.5063687562942505,
1079
+ "eval_ppl": 1.6593,
1080
+ "eval_runtime": 141.112,
1081
+ "eval_samples_per_second": 5.173,
1082
+ "eval_steps_per_second": 1.035,
1083
+ "memory/device_reserved (GiB)": 139.06,
1084
+ "memory/max_active (GiB)": 19.1,
1085
+ "memory/max_allocated (GiB)": 19.1,
1086
+ "step": 2000
1087
+ }
1088
+ ],
1089
+ "logging_steps": 25,
1090
+ "max_steps": 3996,
1091
+ "num_input_tokens_seen": 0,
1092
+ "num_train_epochs": 3,
1093
+ "save_steps": 1000,
1094
+ "stateful_callbacks": {
1095
+ "TrainerControl": {
1096
+ "args": {
1097
+ "should_epoch_stop": false,
1098
+ "should_evaluate": false,
1099
+ "should_log": false,
1100
+ "should_save": true,
1101
+ "should_training_stop": false
1102
+ },
1103
+ "attributes": {}
1104
+ }
1105
+ },
1106
+ "total_flos": 1.62796004179968e+18,
1107
+ "train_batch_size": 5,
1108
+ "trial_name": null,
1109
+ "trial_params": null
1110
+ }
checkpoint-2000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a75cafa9afe18e1aa48e766453f03add03ceb5dd78011703e6068968ae04eab2
3
+ size 7761
checkpoint-3000/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: codellama/CodeLlama-7b-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:codellama/CodeLlama-7b-hf
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- 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. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ 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).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.18.0
checkpoint-3000/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "codellama/CodeLlama-7b-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
9
+ "ensure_weight_tying": false,
10
+ "eva_config": null,
11
+ "exclude_modules": null,
12
+ "fan_in_fan_out": null,
13
+ "inference_mode": true,
14
+ "init_lora_weights": true,
15
+ "layer_replication": null,
16
+ "layers_pattern": null,
17
+ "layers_to_transform": null,
18
+ "loftq_config": {},
19
+ "lora_alpha": 32,
20
+ "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
+ "megatron_config": null,
23
+ "megatron_core": "megatron.core",
24
+ "modules_to_save": null,
25
+ "peft_type": "LORA",
26
+ "peft_version": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "o_proj",
33
+ "v_proj",
34
+ "k_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": [],
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-3000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b4f5f1ada7c250db48cba2e238791cdb7014809135a500d875060d02a931d53e
3
+ size 67143296
checkpoint-3000/chat_template.jinja ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
2
+
3
+ '+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
4
+
5
+ ' }}{% endif %}
checkpoint-3000/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:20304343455a8fd488379728c67bf039255771ac30db5a1d3a9260acecb9f9b8
3
+ size 134433995
checkpoint-3000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c5a2fdb47ec839a29b69def75adfef309f87d753c90579b6aaac5f1d4be8e923
3
+ size 14645
checkpoint-3000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c0d3d381187345aa455213a26a4e087c224775b41b6b4866e6c4ddd1abcdf5f
3
+ size 1465
checkpoint-3000/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-3000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
3
+ size 500058
checkpoint-3000/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": true,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false,
43
+ "use_fast": true
44
+ }
checkpoint-3000/trainer_state.json ADDED
@@ -0,0 +1,1642 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.250562640660165,
6
+ "eval_steps": 1000,
7
+ "global_step": 3000,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0,
14
+ "eval_loss": 1.6887853145599365,
15
+ "eval_ppl": 5.4129,
16
+ "eval_runtime": 167.3526,
17
+ "eval_samples_per_second": 4.362,
18
+ "eval_steps_per_second": 0.872,
19
+ "memory/device_reserved (GiB)": 139.12,
20
+ "memory/max_active (GiB)": 18.94,
21
+ "memory/max_allocated (GiB)": 18.94,
22
+ "step": 0
23
+ },
24
+ {
25
+ "epoch": 0.018754688672168042,
26
+ "grad_norm": 1.415561556816101,
27
+ "learning_rate": 4.8e-05,
28
+ "loss": 1.6848,
29
+ "memory/device_reserved (GiB)": 139.11,
30
+ "memory/max_active (GiB)": 25.53,
31
+ "memory/max_allocated (GiB)": 25.53,
32
+ "ppl": 5.3914,
33
+ "step": 25,
34
+ "tokens_per_second_per_gpu": 16277.76,
35
+ "total_tokens": 1723633
36
+ },
37
+ {
38
+ "epoch": 0.037509377344336084,
39
+ "grad_norm": 0.33179354667663574,
40
+ "learning_rate": 9.8e-05,
41
+ "loss": 0.9839,
42
+ "memory/device_reserved (GiB)": 139.06,
43
+ "memory/max_active (GiB)": 25.53,
44
+ "memory/max_allocated (GiB)": 25.53,
45
+ "ppl": 2.6749,
46
+ "step": 50,
47
+ "tokens_per_second_per_gpu": 4303.21,
48
+ "total_tokens": 2175386
49
+ },
50
+ {
51
+ "epoch": 0.056264066016504126,
52
+ "grad_norm": 0.17453454434871674,
53
+ "learning_rate": 0.000148,
54
+ "loss": 0.8002,
55
+ "memory/device_reserved (GiB)": 139.06,
56
+ "memory/max_active (GiB)": 25.53,
57
+ "memory/max_allocated (GiB)": 25.53,
58
+ "ppl": 2.226,
59
+ "step": 75,
60
+ "tokens_per_second_per_gpu": 3776.03,
61
+ "total_tokens": 2623712
62
+ },
63
+ {
64
+ "epoch": 0.07501875468867217,
65
+ "grad_norm": 0.19318008422851562,
66
+ "learning_rate": 0.00019800000000000002,
67
+ "loss": 0.7218,
68
+ "memory/device_reserved (GiB)": 139.06,
69
+ "memory/max_active (GiB)": 25.53,
70
+ "memory/max_allocated (GiB)": 25.53,
71
+ "ppl": 2.0581,
72
+ "step": 100,
73
+ "tokens_per_second_per_gpu": 4252.49,
74
+ "total_tokens": 3072519
75
+ },
76
+ {
77
+ "epoch": 0.09377344336084022,
78
+ "grad_norm": 0.18435686826705933,
79
+ "learning_rate": 0.00019998127418269004,
80
+ "loss": 0.6759,
81
+ "memory/device_reserved (GiB)": 139.06,
82
+ "memory/max_active (GiB)": 25.53,
83
+ "memory/max_allocated (GiB)": 25.53,
84
+ "ppl": 1.9658,
85
+ "step": 125,
86
+ "tokens_per_second_per_gpu": 4303.31,
87
+ "total_tokens": 3523983
88
+ },
89
+ {
90
+ "epoch": 0.11252813203300825,
91
+ "grad_norm": 0.19870473444461823,
92
+ "learning_rate": 0.00019992195096972548,
93
+ "loss": 0.6703,
94
+ "memory/device_reserved (GiB)": 139.06,
95
+ "memory/max_active (GiB)": 25.53,
96
+ "memory/max_allocated (GiB)": 25.53,
97
+ "ppl": 1.9548,
98
+ "step": 150,
99
+ "tokens_per_second_per_gpu": 4260.86,
100
+ "total_tokens": 3973452
101
+ },
102
+ {
103
+ "epoch": 0.1312828207051763,
104
+ "grad_norm": 0.20499658584594727,
105
+ "learning_rate": 0.0001998220219574743,
106
+ "loss": 0.6381,
107
+ "memory/device_reserved (GiB)": 139.06,
108
+ "memory/max_active (GiB)": 25.53,
109
+ "memory/max_allocated (GiB)": 25.53,
110
+ "ppl": 1.8929,
111
+ "step": 175,
112
+ "tokens_per_second_per_gpu": 4288.64,
113
+ "total_tokens": 4423763
114
+ },
115
+ {
116
+ "epoch": 0.15003750937734434,
117
+ "grad_norm": 0.18934418261051178,
118
+ "learning_rate": 0.00019968152775460537,
119
+ "loss": 0.6383,
120
+ "memory/device_reserved (GiB)": 139.06,
121
+ "memory/max_active (GiB)": 25.53,
122
+ "memory/max_allocated (GiB)": 25.53,
123
+ "ppl": 1.8933,
124
+ "step": 200,
125
+ "tokens_per_second_per_gpu": 4244.79,
126
+ "total_tokens": 4872365
127
+ },
128
+ {
129
+ "epoch": 0.16879219804951237,
130
+ "grad_norm": 0.1827855408191681,
131
+ "learning_rate": 0.00019950052545447352,
132
+ "loss": 0.6347,
133
+ "memory/device_reserved (GiB)": 139.06,
134
+ "memory/max_active (GiB)": 25.53,
135
+ "memory/max_allocated (GiB)": 25.53,
136
+ "ppl": 1.8865,
137
+ "step": 225,
138
+ "tokens_per_second_per_gpu": 4252.71,
139
+ "total_tokens": 5319322
140
+ },
141
+ {
142
+ "epoch": 0.18754688672168043,
143
+ "grad_norm": 0.16483066976070404,
144
+ "learning_rate": 0.00019927908861191827,
145
+ "loss": 0.6392,
146
+ "memory/device_reserved (GiB)": 139.06,
147
+ "memory/max_active (GiB)": 25.53,
148
+ "memory/max_allocated (GiB)": 25.53,
149
+ "ppl": 1.895,
150
+ "step": 250,
151
+ "tokens_per_second_per_gpu": 3772.0,
152
+ "total_tokens": 5768644
153
+ },
154
+ {
155
+ "epoch": 0.20630157539384847,
156
+ "grad_norm": 0.17186357080936432,
157
+ "learning_rate": 0.00019901730721337302,
158
+ "loss": 0.614,
159
+ "memory/device_reserved (GiB)": 139.06,
160
+ "memory/max_active (GiB)": 25.53,
161
+ "memory/max_allocated (GiB)": 25.53,
162
+ "ppl": 1.8478,
163
+ "step": 275,
164
+ "tokens_per_second_per_gpu": 4281.82,
165
+ "total_tokens": 6220751
166
+ },
167
+ {
168
+ "epoch": 0.2250562640660165,
169
+ "grad_norm": 0.18073013424873352,
170
+ "learning_rate": 0.00019871528764029667,
171
+ "loss": 0.6196,
172
+ "memory/device_reserved (GiB)": 139.06,
173
+ "memory/max_active (GiB)": 25.53,
174
+ "memory/max_allocated (GiB)": 25.53,
175
+ "ppl": 1.8582,
176
+ "step": 300,
177
+ "tokens_per_second_per_gpu": 4234.51,
178
+ "total_tokens": 6668111
179
+ },
180
+ {
181
+ "epoch": 0.24381095273818454,
182
+ "grad_norm": 0.19639697670936584,
183
+ "learning_rate": 0.00019837315262594306,
184
+ "loss": 0.6181,
185
+ "memory/device_reserved (GiB)": 139.06,
186
+ "memory/max_active (GiB)": 25.53,
187
+ "memory/max_allocated (GiB)": 25.53,
188
+ "ppl": 1.8554,
189
+ "step": 325,
190
+ "tokens_per_second_per_gpu": 4261.44,
191
+ "total_tokens": 7117439
192
+ },
193
+ {
194
+ "epoch": 0.2625656414103526,
195
+ "grad_norm": 0.1670486479997635,
196
+ "learning_rate": 0.00019799104120548492,
197
+ "loss": 0.6141,
198
+ "memory/device_reserved (GiB)": 139.06,
199
+ "memory/max_active (GiB)": 25.53,
200
+ "memory/max_allocated (GiB)": 25.53,
201
+ "ppl": 1.848,
202
+ "step": 350,
203
+ "tokens_per_second_per_gpu": 4298.97,
204
+ "total_tokens": 7569060
205
+ },
206
+ {
207
+ "epoch": 0.2813203300825206,
208
+ "grad_norm": 0.17752495408058167,
209
+ "learning_rate": 0.00019756910865951377,
210
+ "loss": 0.6075,
211
+ "memory/device_reserved (GiB)": 139.06,
212
+ "memory/max_active (GiB)": 25.53,
213
+ "memory/max_allocated (GiB)": 25.53,
214
+ "ppl": 1.8358,
215
+ "step": 375,
216
+ "tokens_per_second_per_gpu": 4256.6,
217
+ "total_tokens": 8017630
218
+ },
219
+ {
220
+ "epoch": 0.30007501875468867,
221
+ "grad_norm": 0.2000180035829544,
222
+ "learning_rate": 0.00019710752645093747,
223
+ "loss": 0.6108,
224
+ "memory/device_reserved (GiB)": 139.06,
225
+ "memory/max_active (GiB)": 25.53,
226
+ "memory/max_allocated (GiB)": 25.53,
227
+ "ppl": 1.8419,
228
+ "step": 400,
229
+ "tokens_per_second_per_gpu": 4245.46,
230
+ "total_tokens": 8464998
231
+ },
232
+ {
233
+ "epoch": 0.31882970742685673,
234
+ "grad_norm": 0.17395919561386108,
235
+ "learning_rate": 0.00019660648215530206,
236
+ "loss": 0.5966,
237
+ "memory/device_reserved (GiB)": 139.06,
238
+ "memory/max_active (GiB)": 25.53,
239
+ "memory/max_allocated (GiB)": 25.53,
240
+ "ppl": 1.8159,
241
+ "step": 425,
242
+ "tokens_per_second_per_gpu": 3758.92,
243
+ "total_tokens": 8914723
244
+ },
245
+ {
246
+ "epoch": 0.33758439609902474,
247
+ "grad_norm": 0.18785236775875092,
248
+ "learning_rate": 0.00019606617938456572,
249
+ "loss": 0.6099,
250
+ "memory/device_reserved (GiB)": 139.06,
251
+ "memory/max_active (GiB)": 25.53,
252
+ "memory/max_allocated (GiB)": 25.53,
253
+ "ppl": 1.8402,
254
+ "step": 450,
255
+ "tokens_per_second_per_gpu": 4200.53,
256
+ "total_tokens": 9359638
257
+ },
258
+ {
259
+ "epoch": 0.3563390847711928,
260
+ "grad_norm": 0.17702797055244446,
261
+ "learning_rate": 0.0001954868377043559,
262
+ "loss": 0.5922,
263
+ "memory/device_reserved (GiB)": 139.06,
264
+ "memory/max_active (GiB)": 25.53,
265
+ "memory/max_allocated (GiB)": 25.53,
266
+ "ppl": 1.808,
267
+ "step": 475,
268
+ "tokens_per_second_per_gpu": 4265.36,
269
+ "total_tokens": 9810837
270
+ },
271
+ {
272
+ "epoch": 0.37509377344336087,
273
+ "grad_norm": 0.19927558302879333,
274
+ "learning_rate": 0.00019486869254474337,
275
+ "loss": 0.5759,
276
+ "memory/device_reserved (GiB)": 139.06,
277
+ "memory/max_active (GiB)": 25.53,
278
+ "memory/max_allocated (GiB)": 25.53,
279
+ "ppl": 1.7787,
280
+ "step": 500,
281
+ "tokens_per_second_per_gpu": 4276.25,
282
+ "total_tokens": 10261446
283
+ },
284
+ {
285
+ "epoch": 0.3938484621155289,
286
+ "grad_norm": 0.1908370852470398,
287
+ "learning_rate": 0.0001942119951045692,
288
+ "loss": 0.584,
289
+ "memory/device_reserved (GiB)": 139.06,
290
+ "memory/max_active (GiB)": 25.53,
291
+ "memory/max_allocated (GiB)": 25.53,
292
+ "ppl": 1.7932,
293
+ "step": 525,
294
+ "tokens_per_second_per_gpu": 4272.28,
295
+ "total_tokens": 10707841
296
+ },
297
+ {
298
+ "epoch": 0.41260315078769694,
299
+ "grad_norm": 0.2064146101474762,
300
+ "learning_rate": 0.00019351701224936383,
301
+ "loss": 0.5791,
302
+ "memory/device_reserved (GiB)": 139.06,
303
+ "memory/max_active (GiB)": 25.53,
304
+ "memory/max_allocated (GiB)": 25.53,
305
+ "ppl": 1.7844,
306
+ "step": 550,
307
+ "tokens_per_second_per_gpu": 4250.37,
308
+ "total_tokens": 11155384
309
+ },
310
+ {
311
+ "epoch": 0.43135783945986494,
312
+ "grad_norm": 0.26748332381248474,
313
+ "learning_rate": 0.0001927840264028995,
314
+ "loss": 0.5758,
315
+ "memory/device_reserved (GiB)": 139.06,
316
+ "memory/max_active (GiB)": 25.53,
317
+ "memory/max_allocated (GiB)": 25.53,
318
+ "ppl": 1.7786,
319
+ "step": 575,
320
+ "tokens_per_second_per_gpu": 4256.55,
321
+ "total_tokens": 11601192
322
+ },
323
+ {
324
+ "epoch": 0.450112528132033,
325
+ "grad_norm": 0.17514832317829132,
326
+ "learning_rate": 0.00019201333543242036,
327
+ "loss": 0.5791,
328
+ "memory/device_reserved (GiB)": 139.06,
329
+ "memory/max_active (GiB)": 25.53,
330
+ "memory/max_allocated (GiB)": 25.53,
331
+ "ppl": 1.7844,
332
+ "step": 600,
333
+ "tokens_per_second_per_gpu": 3770.83,
334
+ "total_tokens": 12048477
335
+ },
336
+ {
337
+ "epoch": 0.46886721680420107,
338
+ "grad_norm": 0.22069169580936432,
339
+ "learning_rate": 0.00019120525252759647,
340
+ "loss": 0.5803,
341
+ "memory/device_reserved (GiB)": 139.06,
342
+ "memory/max_active (GiB)": 25.53,
343
+ "memory/max_allocated (GiB)": 25.53,
344
+ "ppl": 1.7866,
345
+ "step": 625,
346
+ "tokens_per_second_per_gpu": 4179.31,
347
+ "total_tokens": 12488141
348
+ },
349
+ {
350
+ "epoch": 0.4876219054763691,
351
+ "grad_norm": 0.20555566251277924,
352
+ "learning_rate": 0.00019036010607325138,
353
+ "loss": 0.5716,
354
+ "memory/device_reserved (GiB)": 139.06,
355
+ "memory/max_active (GiB)": 25.53,
356
+ "memory/max_allocated (GiB)": 25.53,
357
+ "ppl": 1.7711,
358
+ "step": 650,
359
+ "tokens_per_second_per_gpu": 4209.96,
360
+ "total_tokens": 12934358
361
+ },
362
+ {
363
+ "epoch": 0.5063765941485371,
364
+ "grad_norm": 0.19018156826496124,
365
+ "learning_rate": 0.00018947823951591478,
366
+ "loss": 0.5608,
367
+ "memory/device_reserved (GiB)": 139.06,
368
+ "memory/max_active (GiB)": 25.53,
369
+ "memory/max_allocated (GiB)": 25.53,
370
+ "ppl": 1.7521,
371
+ "step": 675,
372
+ "tokens_per_second_per_gpu": 4226.4,
373
+ "total_tokens": 13378983
374
+ },
375
+ {
376
+ "epoch": 0.5251312828207052,
377
+ "grad_norm": 0.17173859477043152,
378
+ "learning_rate": 0.00018856001122425416,
379
+ "loss": 0.5667,
380
+ "memory/device_reserved (GiB)": 139.06,
381
+ "memory/max_active (GiB)": 25.53,
382
+ "memory/max_allocated (GiB)": 25.53,
383
+ "ppl": 1.7624,
384
+ "step": 700,
385
+ "tokens_per_second_per_gpu": 4265.57,
386
+ "total_tokens": 13829519
387
+ },
388
+ {
389
+ "epoch": 0.5438859714928732,
390
+ "grad_norm": 0.17706550657749176,
391
+ "learning_rate": 0.0001876057943434428,
392
+ "loss": 0.565,
393
+ "memory/device_reserved (GiB)": 139.06,
394
+ "memory/max_active (GiB)": 25.53,
395
+ "memory/max_allocated (GiB)": 25.53,
396
+ "ppl": 1.7594,
397
+ "step": 725,
398
+ "tokens_per_second_per_gpu": 4281.61,
399
+ "total_tokens": 14281879
400
+ },
401
+ {
402
+ "epoch": 0.5626406601650412,
403
+ "grad_norm": 0.18528586626052856,
404
+ "learning_rate": 0.00018661597664352284,
405
+ "loss": 0.5666,
406
+ "memory/device_reserved (GiB)": 139.06,
407
+ "memory/max_active (GiB)": 25.53,
408
+ "memory/max_allocated (GiB)": 25.53,
409
+ "ppl": 1.7623,
410
+ "step": 750,
411
+ "tokens_per_second_per_gpu": 4229.32,
412
+ "total_tokens": 14725919
413
+ },
414
+ {
415
+ "epoch": 0.5813953488372093,
416
+ "grad_norm": 0.16790929436683655,
417
+ "learning_rate": 0.00018559096036182516,
418
+ "loss": 0.5633,
419
+ "memory/device_reserved (GiB)": 139.06,
420
+ "memory/max_active (GiB)": 25.53,
421
+ "memory/max_allocated (GiB)": 25.53,
422
+ "ppl": 1.7565,
423
+ "step": 775,
424
+ "tokens_per_second_per_gpu": 3775.0,
425
+ "total_tokens": 15175146
426
+ },
427
+ {
428
+ "epoch": 0.6001500375093773,
429
+ "grad_norm": 0.17511805891990662,
430
+ "learning_rate": 0.00018453116203951005,
431
+ "loss": 0.5664,
432
+ "memory/device_reserved (GiB)": 139.06,
433
+ "memory/max_active (GiB)": 25.53,
434
+ "memory/max_allocated (GiB)": 25.53,
435
+ "ppl": 1.7619,
436
+ "step": 800,
437
+ "tokens_per_second_per_gpu": 4218.07,
438
+ "total_tokens": 15619901
439
+ },
440
+ {
441
+ "epoch": 0.6189047261815454,
442
+ "grad_norm": 0.19853387773036957,
443
+ "learning_rate": 0.0001834370123522954,
444
+ "loss": 0.5646,
445
+ "memory/device_reserved (GiB)": 139.06,
446
+ "memory/max_active (GiB)": 25.53,
447
+ "memory/max_allocated (GiB)": 25.53,
448
+ "ppl": 1.7587,
449
+ "step": 825,
450
+ "tokens_per_second_per_gpu": 4230.84,
451
+ "total_tokens": 16066102
452
+ },
453
+ {
454
+ "epoch": 0.6376594148537135,
455
+ "grad_norm": 0.18872258067131042,
456
+ "learning_rate": 0.00018230895593544056,
457
+ "loss": 0.552,
458
+ "memory/device_reserved (GiB)": 139.06,
459
+ "memory/max_active (GiB)": 25.53,
460
+ "memory/max_allocated (GiB)": 25.53,
461
+ "ppl": 1.7367,
462
+ "step": 850,
463
+ "tokens_per_second_per_gpu": 4222.33,
464
+ "total_tokens": 16510696
465
+ },
466
+ {
467
+ "epoch": 0.6564141035258815,
468
+ "grad_norm": 0.9702818989753723,
469
+ "learning_rate": 0.0001811474512030578,
470
+ "loss": 0.5607,
471
+ "memory/device_reserved (GiB)": 139.06,
472
+ "memory/max_active (GiB)": 25.53,
473
+ "memory/max_allocated (GiB)": 25.53,
474
+ "ppl": 1.7519,
475
+ "step": 875,
476
+ "tokens_per_second_per_gpu": 4200.39,
477
+ "total_tokens": 16953918
478
+ },
479
+ {
480
+ "epoch": 0.6751687921980495,
481
+ "grad_norm": 0.17479568719863892,
482
+ "learning_rate": 0.00017995297016182405,
483
+ "loss": 0.564,
484
+ "memory/device_reserved (GiB)": 139.06,
485
+ "memory/max_active (GiB)": 25.53,
486
+ "memory/max_allocated (GiB)": 25.53,
487
+ "ppl": 1.7577,
488
+ "step": 900,
489
+ "tokens_per_second_per_gpu": 4210.15,
490
+ "total_tokens": 17396453
491
+ },
492
+ {
493
+ "epoch": 0.6939234808702176,
494
+ "grad_norm": 0.1948954463005066,
495
+ "learning_rate": 0.0001787259982191692,
496
+ "loss": 0.5511,
497
+ "memory/device_reserved (GiB)": 139.06,
498
+ "memory/max_active (GiB)": 25.53,
499
+ "memory/max_allocated (GiB)": 25.53,
500
+ "ppl": 1.7352,
501
+ "step": 925,
502
+ "tokens_per_second_per_gpu": 4237.98,
503
+ "total_tokens": 17841287
504
+ },
505
+ {
506
+ "epoch": 0.7126781695423856,
507
+ "grad_norm": 0.19541053473949432,
508
+ "learning_rate": 0.00017746703398601872,
509
+ "loss": 0.5532,
510
+ "memory/device_reserved (GiB)": 139.06,
511
+ "memory/max_active (GiB)": 25.53,
512
+ "memory/max_allocated (GiB)": 25.53,
513
+ "ppl": 1.7388,
514
+ "step": 950,
515
+ "tokens_per_second_per_gpu": 3725.33,
516
+ "total_tokens": 18283596
517
+ },
518
+ {
519
+ "epoch": 0.7314328582145536,
520
+ "grad_norm": 0.1818365603685379,
521
+ "learning_rate": 0.0001761765890741701,
522
+ "loss": 0.5521,
523
+ "memory/device_reserved (GiB)": 139.06,
524
+ "memory/max_active (GiB)": 25.53,
525
+ "memory/max_allocated (GiB)": 25.53,
526
+ "ppl": 1.7369,
527
+ "step": 975,
528
+ "tokens_per_second_per_gpu": 4211.63,
529
+ "total_tokens": 18726722
530
+ },
531
+ {
532
+ "epoch": 0.7501875468867217,
533
+ "grad_norm": 0.1838025599718094,
534
+ "learning_rate": 0.00017485518788838705,
535
+ "loss": 0.5511,
536
+ "memory/device_reserved (GiB)": 139.06,
537
+ "memory/max_active (GiB)": 25.53,
538
+ "memory/max_allocated (GiB)": 25.53,
539
+ "ppl": 1.7352,
540
+ "step": 1000,
541
+ "tokens_per_second_per_gpu": 3962.4,
542
+ "total_tokens": 19167258
543
+ },
544
+ {
545
+ "epoch": 0.7501875468867217,
546
+ "eval_loss": 0.540988564491272,
547
+ "eval_ppl": 1.7177,
548
+ "eval_runtime": 138.0264,
549
+ "eval_samples_per_second": 5.289,
550
+ "eval_steps_per_second": 1.058,
551
+ "memory/device_reserved (GiB)": 139.02,
552
+ "memory/max_active (GiB)": 19.1,
553
+ "memory/max_allocated (GiB)": 19.1,
554
+ "step": 1000
555
+ },
556
+ {
557
+ "epoch": 0.7689422355588897,
558
+ "grad_norm": 0.2199818342924118,
559
+ "learning_rate": 0.00017350336741329413,
560
+ "loss": 0.549,
561
+ "memory/device_reserved (GiB)": 139.06,
562
+ "memory/max_active (GiB)": 25.53,
563
+ "memory/max_allocated (GiB)": 25.53,
564
+ "ppl": 1.7315,
565
+ "step": 1025,
566
+ "tokens_per_second_per_gpu": 4129.73,
567
+ "total_tokens": 20870820
568
+ },
569
+ {
570
+ "epoch": 0.7876969242310577,
571
+ "grad_norm": 0.19783177971839905,
572
+ "learning_rate": 0.0001721216769951596,
573
+ "loss": 0.5615,
574
+ "memory/device_reserved (GiB)": 139.06,
575
+ "memory/max_active (GiB)": 25.53,
576
+ "memory/max_allocated (GiB)": 25.53,
577
+ "ppl": 1.7533,
578
+ "step": 1050,
579
+ "tokens_per_second_per_gpu": 4243.63,
580
+ "total_tokens": 21317982
581
+ },
582
+ {
583
+ "epoch": 0.8064516129032258,
584
+ "grad_norm": 0.1678430140018463,
585
+ "learning_rate": 0.00017071067811865476,
586
+ "loss": 0.5557,
587
+ "memory/device_reserved (GiB)": 139.06,
588
+ "memory/max_active (GiB)": 25.53,
589
+ "memory/max_allocated (GiB)": 25.53,
590
+ "ppl": 1.7432,
591
+ "step": 1075,
592
+ "tokens_per_second_per_gpu": 4092.04,
593
+ "total_tokens": 21754087
594
+ },
595
+ {
596
+ "epoch": 0.8252063015753939,
597
+ "grad_norm": 0.16523879766464233,
598
+ "learning_rate": 0.00016927094417868048,
599
+ "loss": 0.556,
600
+ "memory/device_reserved (GiB)": 139.06,
601
+ "memory/max_active (GiB)": 25.53,
602
+ "memory/max_allocated (GiB)": 25.53,
603
+ "ppl": 1.7437,
604
+ "step": 1100,
605
+ "tokens_per_second_per_gpu": 4187.02,
606
+ "total_tokens": 22198779
607
+ },
608
+ {
609
+ "epoch": 0.8439609902475619,
610
+ "grad_norm": 0.18177717924118042,
611
+ "learning_rate": 0.00016780306024735382,
612
+ "loss": 0.5468,
613
+ "memory/device_reserved (GiB)": 139.06,
614
+ "memory/max_active (GiB)": 25.53,
615
+ "memory/max_allocated (GiB)": 25.53,
616
+ "ppl": 1.7277,
617
+ "step": 1125,
618
+ "tokens_per_second_per_gpu": 4198.97,
619
+ "total_tokens": 22639769
620
+ },
621
+ {
622
+ "epoch": 0.8627156789197299,
623
+ "grad_norm": 0.17299720644950867,
624
+ "learning_rate": 0.0001663076228362492,
625
+ "loss": 0.554,
626
+ "memory/device_reserved (GiB)": 139.06,
627
+ "memory/max_active (GiB)": 25.53,
628
+ "memory/max_allocated (GiB)": 25.53,
629
+ "ppl": 1.7402,
630
+ "step": 1150,
631
+ "tokens_per_second_per_gpu": 3762.13,
632
+ "total_tokens": 23086742
633
+ },
634
+ {
635
+ "epoch": 0.881470367591898,
636
+ "grad_norm": 0.19112971425056458,
637
+ "learning_rate": 0.00016478523965399085,
638
+ "loss": 0.5434,
639
+ "memory/device_reserved (GiB)": 139.06,
640
+ "memory/max_active (GiB)": 25.53,
641
+ "memory/max_allocated (GiB)": 25.53,
642
+ "ppl": 1.7219,
643
+ "step": 1175,
644
+ "tokens_per_second_per_gpu": 4205.37,
645
+ "total_tokens": 23528106
646
+ },
647
+ {
648
+ "epoch": 0.900225056264066,
649
+ "grad_norm": 0.17930163443088531,
650
+ "learning_rate": 0.00016323652935929536,
651
+ "loss": 0.5362,
652
+ "memory/device_reserved (GiB)": 139.06,
653
+ "memory/max_active (GiB)": 25.53,
654
+ "memory/max_allocated (GiB)": 25.53,
655
+ "ppl": 1.7095,
656
+ "step": 1200,
657
+ "tokens_per_second_per_gpu": 4228.83,
658
+ "total_tokens": 23974427
659
+ },
660
+ {
661
+ "epoch": 0.918979744936234,
662
+ "grad_norm": 0.18718039989471436,
663
+ "learning_rate": 0.00016166212130956382,
664
+ "loss": 0.5533,
665
+ "memory/device_reserved (GiB)": 139.06,
666
+ "memory/max_active (GiB)": 25.53,
667
+ "memory/max_allocated (GiB)": 25.53,
668
+ "ppl": 1.739,
669
+ "step": 1225,
670
+ "tokens_per_second_per_gpu": 4211.64,
671
+ "total_tokens": 24415919
672
+ },
673
+ {
674
+ "epoch": 0.9377344336084021,
675
+ "grad_norm": 0.17105573415756226,
676
+ "learning_rate": 0.0001600626553051268,
677
+ "loss": 0.5492,
678
+ "memory/device_reserved (GiB)": 139.06,
679
+ "memory/max_active (GiB)": 25.53,
680
+ "memory/max_allocated (GiB)": 25.53,
681
+ "ppl": 1.7319,
682
+ "step": 1250,
683
+ "tokens_per_second_per_gpu": 4183.86,
684
+ "total_tokens": 24854345
685
+ },
686
+ {
687
+ "epoch": 0.9564891222805701,
688
+ "grad_norm": 0.1733955442905426,
689
+ "learning_rate": 0.0001584387813292454,
690
+ "loss": 0.5348,
691
+ "memory/device_reserved (GiB)": 139.06,
692
+ "memory/max_active (GiB)": 25.53,
693
+ "memory/max_allocated (GiB)": 25.53,
694
+ "ppl": 1.7071,
695
+ "step": 1275,
696
+ "tokens_per_second_per_gpu": 4172.93,
697
+ "total_tokens": 25292647
698
+ },
699
+ {
700
+ "epoch": 0.9752438109527382,
701
+ "grad_norm": 0.1858205944299698,
702
+ "learning_rate": 0.00015679115928397401,
703
+ "loss": 0.5527,
704
+ "memory/device_reserved (GiB)": 139.06,
705
+ "memory/max_active (GiB)": 25.53,
706
+ "memory/max_allocated (GiB)": 25.53,
707
+ "ppl": 1.7379,
708
+ "step": 1300,
709
+ "tokens_per_second_per_gpu": 4226.34,
710
+ "total_tokens": 25733591
711
+ },
712
+ {
713
+ "epoch": 0.9939984996249063,
714
+ "grad_norm": 0.1944192498922348,
715
+ "learning_rate": 0.00015512045872199276,
716
+ "loss": 0.5311,
717
+ "memory/device_reserved (GiB)": 139.06,
718
+ "memory/max_active (GiB)": 25.53,
719
+ "memory/max_allocated (GiB)": 25.53,
720
+ "ppl": 1.7008,
721
+ "step": 1325,
722
+ "tokens_per_second_per_gpu": 3655.12,
723
+ "total_tokens": 26164528
724
+ },
725
+ {
726
+ "epoch": 1.0127531882970742,
727
+ "grad_norm": 0.18358173966407776,
728
+ "learning_rate": 0.00015342735857451777,
729
+ "loss": 0.5145,
730
+ "memory/device_reserved (GiB)": 139.06,
731
+ "memory/max_active (GiB)": 25.53,
732
+ "memory/max_allocated (GiB)": 25.53,
733
+ "ppl": 1.6728,
734
+ "step": 1350,
735
+ "tokens_per_second_per_gpu": 4227.25,
736
+ "total_tokens": 26610460
737
+ },
738
+ {
739
+ "epoch": 1.0315078769692423,
740
+ "grad_norm": 0.1853465735912323,
741
+ "learning_rate": 0.00015171254687540038,
742
+ "loss": 0.5081,
743
+ "memory/device_reserved (GiB)": 139.06,
744
+ "memory/max_active (GiB)": 25.53,
745
+ "memory/max_allocated (GiB)": 25.53,
746
+ "ppl": 1.6621,
747
+ "step": 1375,
748
+ "tokens_per_second_per_gpu": 4318.88,
749
+ "total_tokens": 27064008
750
+ },
751
+ {
752
+ "epoch": 1.0502625656414104,
753
+ "grad_norm": 0.18925060331821442,
754
+ "learning_rate": 0.0001499767204815273,
755
+ "loss": 0.5185,
756
+ "memory/device_reserved (GiB)": 139.06,
757
+ "memory/max_active (GiB)": 25.53,
758
+ "memory/max_allocated (GiB)": 25.53,
759
+ "ppl": 1.6795,
760
+ "step": 1400,
761
+ "tokens_per_second_per_gpu": 4324.01,
762
+ "total_tokens": 27516590
763
+ },
764
+ {
765
+ "epoch": 1.0690172543135783,
766
+ "grad_norm": 0.20961470901966095,
767
+ "learning_rate": 0.00014822058478963532,
768
+ "loss": 0.5234,
769
+ "memory/device_reserved (GiB)": 139.06,
770
+ "memory/max_active (GiB)": 25.53,
771
+ "memory/max_allocated (GiB)": 25.53,
772
+ "ppl": 1.6878,
773
+ "step": 1425,
774
+ "tokens_per_second_per_gpu": 4319.64,
775
+ "total_tokens": 27970075
776
+ },
777
+ {
778
+ "epoch": 1.0877719429857464,
779
+ "grad_norm": 0.1982697695493698,
780
+ "learning_rate": 0.0001464448534496555,
781
+ "loss": 0.5169,
782
+ "memory/device_reserved (GiB)": 139.06,
783
+ "memory/max_active (GiB)": 25.53,
784
+ "memory/max_allocated (GiB)": 25.53,
785
+ "ppl": 1.6768,
786
+ "step": 1450,
787
+ "tokens_per_second_per_gpu": 4267.88,
788
+ "total_tokens": 28419716
789
+ },
790
+ {
791
+ "epoch": 1.1065266316579145,
792
+ "grad_norm": 0.1925143301486969,
793
+ "learning_rate": 0.00014465024807470376,
794
+ "loss": 0.5197,
795
+ "memory/device_reserved (GiB)": 139.06,
796
+ "memory/max_active (GiB)": 25.53,
797
+ "memory/max_allocated (GiB)": 25.53,
798
+ "ppl": 1.6815,
799
+ "step": 1475,
800
+ "tokens_per_second_per_gpu": 4264.53,
801
+ "total_tokens": 28866312
802
+ },
803
+ {
804
+ "epoch": 1.1252813203300824,
805
+ "grad_norm": 0.18788637220859528,
806
+ "learning_rate": 0.0001428374979478349,
807
+ "loss": 0.5204,
808
+ "memory/device_reserved (GiB)": 139.06,
809
+ "memory/max_active (GiB)": 25.53,
810
+ "memory/max_allocated (GiB)": 25.53,
811
+ "ppl": 1.6827,
812
+ "step": 1500,
813
+ "tokens_per_second_per_gpu": 3779.33,
814
+ "total_tokens": 29315968
815
+ },
816
+ {
817
+ "epoch": 1.1440360090022506,
818
+ "grad_norm": 0.18954145908355713,
819
+ "learning_rate": 0.00014100733972568038,
820
+ "loss": 0.5164,
821
+ "memory/device_reserved (GiB)": 139.06,
822
+ "memory/max_active (GiB)": 25.53,
823
+ "memory/max_allocated (GiB)": 25.53,
824
+ "ppl": 1.676,
825
+ "step": 1525,
826
+ "tokens_per_second_per_gpu": 4282.57,
827
+ "total_tokens": 29766723
828
+ },
829
+ {
830
+ "epoch": 1.1627906976744187,
831
+ "grad_norm": 0.19003146886825562,
832
+ "learning_rate": 0.00013916051713908924,
833
+ "loss": 0.5095,
834
+ "memory/device_reserved (GiB)": 139.06,
835
+ "memory/max_active (GiB)": 25.53,
836
+ "memory/max_allocated (GiB)": 25.53,
837
+ "ppl": 1.6645,
838
+ "step": 1550,
839
+ "tokens_per_second_per_gpu": 4290.76,
840
+ "total_tokens": 30218573
841
+ },
842
+ {
843
+ "epoch": 1.1815453863465866,
844
+ "grad_norm": 0.18279583752155304,
845
+ "learning_rate": 0.00013729778069089437,
846
+ "loss": 0.522,
847
+ "memory/device_reserved (GiB)": 139.06,
848
+ "memory/max_active (GiB)": 25.53,
849
+ "memory/max_allocated (GiB)": 25.53,
850
+ "ppl": 1.6854,
851
+ "step": 1575,
852
+ "tokens_per_second_per_gpu": 4300.13,
853
+ "total_tokens": 30669810
854
+ },
855
+ {
856
+ "epoch": 1.2003000750187547,
857
+ "grad_norm": 0.18783092498779297,
858
+ "learning_rate": 0.00013541988735092672,
859
+ "loss": 0.5003,
860
+ "memory/device_reserved (GiB)": 139.06,
861
+ "memory/max_active (GiB)": 25.53,
862
+ "memory/max_allocated (GiB)": 25.53,
863
+ "ppl": 1.6492,
864
+ "step": 1600,
865
+ "tokens_per_second_per_gpu": 4271.27,
866
+ "total_tokens": 31117586
867
+ },
868
+ {
869
+ "epoch": 1.2190547636909228,
870
+ "grad_norm": 0.199558824300766,
871
+ "learning_rate": 0.00013352760024840175,
872
+ "loss": 0.5115,
873
+ "memory/device_reserved (GiB)": 139.06,
874
+ "memory/max_active (GiB)": 25.53,
875
+ "memory/max_allocated (GiB)": 25.53,
876
+ "ppl": 1.6678,
877
+ "step": 1625,
878
+ "tokens_per_second_per_gpu": 4248.14,
879
+ "total_tokens": 31562224
880
+ },
881
+ {
882
+ "epoch": 1.2378094523630907,
883
+ "grad_norm": 0.19465653598308563,
884
+ "learning_rate": 0.00013162168836180246,
885
+ "loss": 0.4967,
886
+ "memory/device_reserved (GiB)": 139.06,
887
+ "memory/max_active (GiB)": 25.53,
888
+ "memory/max_allocated (GiB)": 25.53,
889
+ "ppl": 1.6433,
890
+ "step": 1650,
891
+ "tokens_per_second_per_gpu": 4286.24,
892
+ "total_tokens": 32011071
893
+ },
894
+ {
895
+ "epoch": 1.2565641410352588,
896
+ "grad_norm": 0.2054641842842102,
897
+ "learning_rate": 0.00012970292620638574,
898
+ "loss": 0.5172,
899
+ "memory/device_reserved (GiB)": 139.06,
900
+ "memory/max_active (GiB)": 25.53,
901
+ "memory/max_allocated (GiB)": 25.53,
902
+ "ppl": 1.6773,
903
+ "step": 1675,
904
+ "tokens_per_second_per_gpu": 3733.1,
905
+ "total_tokens": 32452490
906
+ },
907
+ {
908
+ "epoch": 1.275318829707427,
909
+ "grad_norm": 0.19450411200523376,
910
+ "learning_rate": 0.00012777209351943862,
911
+ "loss": 0.5149,
912
+ "memory/device_reserved (GiB)": 139.06,
913
+ "memory/max_active (GiB)": 25.53,
914
+ "memory/max_allocated (GiB)": 25.53,
915
+ "ppl": 1.6735,
916
+ "step": 1700,
917
+ "tokens_per_second_per_gpu": 4251.33,
918
+ "total_tokens": 32899103
919
+ },
920
+ {
921
+ "epoch": 1.2940735183795948,
922
+ "grad_norm": 0.19844166934490204,
923
+ "learning_rate": 0.0001258299749434123,
924
+ "loss": 0.5205,
925
+ "memory/device_reserved (GiB)": 139.06,
926
+ "memory/max_active (GiB)": 25.53,
927
+ "memory/max_allocated (GiB)": 25.53,
928
+ "ppl": 1.6829,
929
+ "step": 1725,
930
+ "tokens_per_second_per_gpu": 4240.57,
931
+ "total_tokens": 33344569
932
+ },
933
+ {
934
+ "epoch": 1.312828207051763,
935
+ "grad_norm": 0.19240470230579376,
936
+ "learning_rate": 0.00012387735970706312,
937
+ "loss": 0.5033,
938
+ "memory/device_reserved (GiB)": 139.06,
939
+ "memory/max_active (GiB)": 25.53,
940
+ "memory/max_allocated (GiB)": 25.53,
941
+ "ppl": 1.6542,
942
+ "step": 1750,
943
+ "tokens_per_second_per_gpu": 4267.65,
944
+ "total_tokens": 33790426
945
+ },
946
+ {
947
+ "epoch": 1.331582895723931,
948
+ "grad_norm": 0.18220192193984985,
949
+ "learning_rate": 0.00012191504130472937,
950
+ "loss": 0.5103,
951
+ "memory/device_reserved (GiB)": 139.06,
952
+ "memory/max_active (GiB)": 25.53,
953
+ "memory/max_allocated (GiB)": 25.53,
954
+ "ppl": 1.6658,
955
+ "step": 1775,
956
+ "tokens_per_second_per_gpu": 4237.08,
957
+ "total_tokens": 34233908
958
+ },
959
+ {
960
+ "epoch": 1.350337584396099,
961
+ "grad_norm": 0.20157551765441895,
962
+ "learning_rate": 0.00011994381717387514,
963
+ "loss": 0.5192,
964
+ "memory/device_reserved (GiB)": 139.06,
965
+ "memory/max_active (GiB)": 25.53,
966
+ "memory/max_allocated (GiB)": 25.53,
967
+ "ppl": 1.6807,
968
+ "step": 1800,
969
+ "tokens_per_second_per_gpu": 4244.09,
970
+ "total_tokens": 34678691
971
+ },
972
+ {
973
+ "epoch": 1.369092273068267,
974
+ "grad_norm": 0.17189238965511322,
975
+ "learning_rate": 0.00011796448837103129,
976
+ "loss": 0.5011,
977
+ "memory/device_reserved (GiB)": 139.06,
978
+ "memory/max_active (GiB)": 25.53,
979
+ "memory/max_allocated (GiB)": 25.53,
980
+ "ppl": 1.6505,
981
+ "step": 1825,
982
+ "tokens_per_second_per_gpu": 4277.26,
983
+ "total_tokens": 35125624
984
+ },
985
+ {
986
+ "epoch": 1.387846961740435,
987
+ "grad_norm": 0.19443106651306152,
988
+ "learning_rate": 0.00011597785924626616,
989
+ "loss": 0.4994,
990
+ "memory/device_reserved (GiB)": 139.06,
991
+ "memory/max_active (GiB)": 25.53,
992
+ "memory/max_allocated (GiB)": 25.53,
993
+ "ppl": 1.6477,
994
+ "step": 1850,
995
+ "tokens_per_second_per_gpu": 3766.52,
996
+ "total_tokens": 35568850
997
+ },
998
+ {
999
+ "epoch": 1.406601650412603,
1000
+ "grad_norm": 0.1810811311006546,
1001
+ "learning_rate": 0.00011398473711631764,
1002
+ "loss": 0.5083,
1003
+ "memory/device_reserved (GiB)": 139.06,
1004
+ "memory/max_active (GiB)": 25.53,
1005
+ "memory/max_allocated (GiB)": 25.53,
1006
+ "ppl": 1.6625,
1007
+ "step": 1875,
1008
+ "tokens_per_second_per_gpu": 4204.76,
1009
+ "total_tokens": 36009980
1010
+ },
1011
+ {
1012
+ "epoch": 1.4253563390847712,
1013
+ "grad_norm": 0.19805970788002014,
1014
+ "learning_rate": 0.00011198593193651958,
1015
+ "loss": 0.5141,
1016
+ "memory/device_reserved (GiB)": 139.06,
1017
+ "memory/max_active (GiB)": 25.53,
1018
+ "memory/max_allocated (GiB)": 25.53,
1019
+ "ppl": 1.6721,
1020
+ "step": 1900,
1021
+ "tokens_per_second_per_gpu": 4270.21,
1022
+ "total_tokens": 36457032
1023
+ },
1024
+ {
1025
+ "epoch": 1.4441110277569393,
1026
+ "grad_norm": 0.1936168372631073,
1027
+ "learning_rate": 0.00010998225597165628,
1028
+ "loss": 0.5045,
1029
+ "memory/device_reserved (GiB)": 139.06,
1030
+ "memory/max_active (GiB)": 25.53,
1031
+ "memory/max_allocated (GiB)": 25.53,
1032
+ "ppl": 1.6562,
1033
+ "step": 1925,
1034
+ "tokens_per_second_per_gpu": 4275.24,
1035
+ "total_tokens": 36905590
1036
+ },
1037
+ {
1038
+ "epoch": 1.4628657164291072,
1039
+ "grad_norm": 0.19065748155117035,
1040
+ "learning_rate": 0.00010797452346587798,
1041
+ "loss": 0.5025,
1042
+ "memory/device_reserved (GiB)": 139.06,
1043
+ "memory/max_active (GiB)": 25.53,
1044
+ "memory/max_allocated (GiB)": 25.53,
1045
+ "ppl": 1.6528,
1046
+ "step": 1950,
1047
+ "tokens_per_second_per_gpu": 4285.81,
1048
+ "total_tokens": 37354436
1049
+ },
1050
+ {
1051
+ "epoch": 1.4816204051012754,
1052
+ "grad_norm": 0.18647657334804535,
1053
+ "learning_rate": 0.0001059635503118125,
1054
+ "loss": 0.5102,
1055
+ "memory/device_reserved (GiB)": 139.06,
1056
+ "memory/max_active (GiB)": 25.53,
1057
+ "memory/max_allocated (GiB)": 25.53,
1058
+ "ppl": 1.6656,
1059
+ "step": 1975,
1060
+ "tokens_per_second_per_gpu": 4259.76,
1061
+ "total_tokens": 37801500
1062
+ },
1063
+ {
1064
+ "epoch": 1.5003750937734432,
1065
+ "grad_norm": 0.21211788058280945,
1066
+ "learning_rate": 0.00010395015371900663,
1067
+ "loss": 0.5052,
1068
+ "memory/device_reserved (GiB)": 139.06,
1069
+ "memory/max_active (GiB)": 25.53,
1070
+ "memory/max_allocated (GiB)": 25.53,
1071
+ "ppl": 1.6573,
1072
+ "step": 2000,
1073
+ "tokens_per_second_per_gpu": 4250.7,
1074
+ "total_tokens": 38244936
1075
+ },
1076
+ {
1077
+ "epoch": 1.5003750937734432,
1078
+ "eval_loss": 0.5063687562942505,
1079
+ "eval_ppl": 1.6593,
1080
+ "eval_runtime": 141.112,
1081
+ "eval_samples_per_second": 5.173,
1082
+ "eval_steps_per_second": 1.035,
1083
+ "memory/device_reserved (GiB)": 139.06,
1084
+ "memory/max_active (GiB)": 19.1,
1085
+ "memory/max_allocated (GiB)": 19.1,
1086
+ "step": 2000
1087
+ },
1088
+ {
1089
+ "epoch": 1.5191297824456114,
1090
+ "grad_norm": 0.20089760422706604,
1091
+ "learning_rate": 0.00010193515188183245,
1092
+ "loss": 0.4892,
1093
+ "memory/device_reserved (GiB)": 139.06,
1094
+ "memory/max_active (GiB)": 25.53,
1095
+ "memory/max_allocated (GiB)": 25.53,
1096
+ "ppl": 1.631,
1097
+ "step": 2025,
1098
+ "tokens_per_second_per_gpu": 4246.58,
1099
+ "total_tokens": 39959888
1100
+ },
1101
+ {
1102
+ "epoch": 1.5378844711177795,
1103
+ "grad_norm": 0.19840118288993835,
1104
+ "learning_rate": 9.991936364699348e-05,
1105
+ "loss": 0.503,
1106
+ "memory/device_reserved (GiB)": 139.06,
1107
+ "memory/max_active (GiB)": 25.53,
1108
+ "memory/max_allocated (GiB)": 25.53,
1109
+ "ppl": 1.6537,
1110
+ "step": 2050,
1111
+ "tokens_per_second_per_gpu": 4320.38,
1112
+ "total_tokens": 40411902
1113
+ },
1114
+ {
1115
+ "epoch": 1.5566391597899476,
1116
+ "grad_norm": 0.20045842230319977,
1117
+ "learning_rate": 9.790360818076577e-05,
1118
+ "loss": 0.5127,
1119
+ "memory/device_reserved (GiB)": 139.06,
1120
+ "memory/max_active (GiB)": 25.53,
1121
+ "memory/max_allocated (GiB)": 25.53,
1122
+ "ppl": 1.6698,
1123
+ "step": 2075,
1124
+ "tokens_per_second_per_gpu": 4245.02,
1125
+ "total_tokens": 40855384
1126
+ },
1127
+ {
1128
+ "epoch": 1.5753938484621155,
1129
+ "grad_norm": 0.19669026136398315,
1130
+ "learning_rate": 9.588870463610893e-05,
1131
+ "loss": 0.4994,
1132
+ "memory/device_reserved (GiB)": 139.06,
1133
+ "memory/max_active (GiB)": 25.53,
1134
+ "memory/max_allocated (GiB)": 25.53,
1135
+ "ppl": 1.6477,
1136
+ "step": 2100,
1137
+ "tokens_per_second_per_gpu": 4174.18,
1138
+ "total_tokens": 41293525
1139
+ },
1140
+ {
1141
+ "epoch": 1.5941485371342836,
1142
+ "grad_norm": 0.19754259288311005,
1143
+ "learning_rate": 9.387547181978291e-05,
1144
+ "loss": 0.5009,
1145
+ "memory/device_reserved (GiB)": 139.06,
1146
+ "memory/max_active (GiB)": 25.53,
1147
+ "memory/max_allocated (GiB)": 25.53,
1148
+ "ppl": 1.6502,
1149
+ "step": 2125,
1150
+ "tokens_per_second_per_gpu": 4200.06,
1151
+ "total_tokens": 41737747
1152
+ },
1153
+ {
1154
+ "epoch": 1.6129032258064515,
1155
+ "grad_norm": 0.19482502341270447,
1156
+ "learning_rate": 9.186472785960507e-05,
1157
+ "loss": 0.5002,
1158
+ "memory/device_reserved (GiB)": 139.06,
1159
+ "memory/max_active (GiB)": 25.53,
1160
+ "memory/max_allocated (GiB)": 25.53,
1161
+ "ppl": 1.6491,
1162
+ "step": 2150,
1163
+ "tokens_per_second_per_gpu": 3696.76,
1164
+ "total_tokens": 42176082
1165
+ },
1166
+ {
1167
+ "epoch": 1.6316579144786196,
1168
+ "grad_norm": 0.21606561541557312,
1169
+ "learning_rate": 8.985728987198352e-05,
1170
+ "loss": 0.4959,
1171
+ "memory/device_reserved (GiB)": 139.06,
1172
+ "memory/max_active (GiB)": 25.53,
1173
+ "memory/max_allocated (GiB)": 25.53,
1174
+ "ppl": 1.642,
1175
+ "step": 2175,
1176
+ "tokens_per_second_per_gpu": 4192.5,
1177
+ "total_tokens": 42616372
1178
+ },
1179
+ {
1180
+ "epoch": 1.6504126031507877,
1181
+ "grad_norm": 0.1979638934135437,
1182
+ "learning_rate": 8.785397362986114e-05,
1183
+ "loss": 0.5031,
1184
+ "memory/device_reserved (GiB)": 139.06,
1185
+ "memory/max_active (GiB)": 25.53,
1186
+ "memory/max_allocated (GiB)": 25.53,
1187
+ "ppl": 1.6538,
1188
+ "step": 2200,
1189
+ "tokens_per_second_per_gpu": 4211.67,
1190
+ "total_tokens": 43058315
1191
+ },
1192
+ {
1193
+ "epoch": 1.6691672918229559,
1194
+ "grad_norm": 0.20717743039131165,
1195
+ "learning_rate": 8.58555932312059e-05,
1196
+ "loss": 0.4986,
1197
+ "memory/device_reserved (GiB)": 139.06,
1198
+ "memory/max_active (GiB)": 25.53,
1199
+ "memory/max_allocated (GiB)": 25.53,
1200
+ "ppl": 1.6464,
1201
+ "step": 2225,
1202
+ "tokens_per_second_per_gpu": 4242.04,
1203
+ "total_tokens": 43501960
1204
+ },
1205
+ {
1206
+ "epoch": 1.6879219804951238,
1207
+ "grad_norm": 0.18736609816551208,
1208
+ "learning_rate": 8.38629607681815e-05,
1209
+ "loss": 0.4898,
1210
+ "memory/device_reserved (GiB)": 139.06,
1211
+ "memory/max_active (GiB)": 25.53,
1212
+ "memory/max_allocated (GiB)": 25.53,
1213
+ "ppl": 1.632,
1214
+ "step": 2250,
1215
+ "tokens_per_second_per_gpu": 4235.21,
1216
+ "total_tokens": 43947235
1217
+ },
1218
+ {
1219
+ "epoch": 1.7066766691672917,
1220
+ "grad_norm": 0.2056591659784317,
1221
+ "learning_rate": 8.187688599713333e-05,
1222
+ "loss": 0.4925,
1223
+ "memory/device_reserved (GiB)": 139.06,
1224
+ "memory/max_active (GiB)": 25.53,
1225
+ "memory/max_allocated (GiB)": 25.53,
1226
+ "ppl": 1.6364,
1227
+ "step": 2275,
1228
+ "tokens_per_second_per_gpu": 4256.41,
1229
+ "total_tokens": 44393451
1230
+ },
1231
+ {
1232
+ "epoch": 1.7254313578394598,
1233
+ "grad_norm": 0.19774597883224487,
1234
+ "learning_rate": 7.989817600952376e-05,
1235
+ "loss": 0.4952,
1236
+ "memory/device_reserved (GiB)": 139.06,
1237
+ "memory/max_active (GiB)": 25.53,
1238
+ "memory/max_allocated (GiB)": 25.53,
1239
+ "ppl": 1.6408,
1240
+ "step": 2300,
1241
+ "tokens_per_second_per_gpu": 4224.5,
1242
+ "total_tokens": 44836590
1243
+ },
1244
+ {
1245
+ "epoch": 1.744186046511628,
1246
+ "grad_norm": 0.19662383198738098,
1247
+ "learning_rate": 7.792763490394984e-05,
1248
+ "loss": 0.4977,
1249
+ "memory/device_reserved (GiB)": 139.06,
1250
+ "memory/max_active (GiB)": 25.53,
1251
+ "memory/max_allocated (GiB)": 25.53,
1252
+ "ppl": 1.6449,
1253
+ "step": 2325,
1254
+ "tokens_per_second_per_gpu": 3741.52,
1255
+ "total_tokens": 45279799
1256
+ },
1257
+ {
1258
+ "epoch": 1.762940735183796,
1259
+ "grad_norm": 0.19400179386138916,
1260
+ "learning_rate": 7.596606345937812e-05,
1261
+ "loss": 0.4965,
1262
+ "memory/device_reserved (GiB)": 139.06,
1263
+ "memory/max_active (GiB)": 25.53,
1264
+ "memory/max_allocated (GiB)": 25.53,
1265
+ "ppl": 1.643,
1266
+ "step": 2350,
1267
+ "tokens_per_second_per_gpu": 4248.51,
1268
+ "total_tokens": 45725602
1269
+ },
1270
+ {
1271
+ "epoch": 1.7816954238559641,
1272
+ "grad_norm": 0.20261766016483307,
1273
+ "learning_rate": 7.401425880972742e-05,
1274
+ "loss": 0.5014,
1275
+ "memory/device_reserved (GiB)": 139.06,
1276
+ "memory/max_active (GiB)": 25.53,
1277
+ "memory/max_allocated (GiB)": 25.53,
1278
+ "ppl": 1.651,
1279
+ "step": 2375,
1280
+ "tokens_per_second_per_gpu": 4216.2,
1281
+ "total_tokens": 46167730
1282
+ },
1283
+ {
1284
+ "epoch": 1.800450112528132,
1285
+ "grad_norm": 0.20447255671024323,
1286
+ "learning_rate": 7.207301411993387e-05,
1287
+ "loss": 0.4901,
1288
+ "memory/device_reserved (GiB)": 139.06,
1289
+ "memory/max_active (GiB)": 25.53,
1290
+ "memory/max_allocated (GiB)": 25.53,
1291
+ "ppl": 1.6325,
1292
+ "step": 2400,
1293
+ "tokens_per_second_per_gpu": 3727.37,
1294
+ "total_tokens": 46611126
1295
+ },
1296
+ {
1297
+ "epoch": 1.8192048012003,
1298
+ "grad_norm": 0.19921696186065674,
1299
+ "learning_rate": 7.014311826362804e-05,
1300
+ "loss": 0.4925,
1301
+ "memory/device_reserved (GiB)": 139.06,
1302
+ "memory/max_active (GiB)": 25.53,
1303
+ "memory/max_allocated (GiB)": 25.53,
1304
+ "ppl": 1.6364,
1305
+ "step": 2425,
1306
+ "tokens_per_second_per_gpu": 4202.19,
1307
+ "total_tokens": 47050763
1308
+ },
1309
+ {
1310
+ "epoch": 1.837959489872468,
1311
+ "grad_norm": 0.20095540583133698,
1312
+ "learning_rate": 6.822535550255652e-05,
1313
+ "loss": 0.494,
1314
+ "memory/device_reserved (GiB)": 139.06,
1315
+ "memory/max_active (GiB)": 25.53,
1316
+ "memory/max_allocated (GiB)": 25.53,
1317
+ "ppl": 1.6389,
1318
+ "step": 2450,
1319
+ "tokens_per_second_per_gpu": 4230.16,
1320
+ "total_tokens": 47496926
1321
+ },
1322
+ {
1323
+ "epoch": 1.8567141785446362,
1324
+ "grad_norm": 0.20210741460323334,
1325
+ "learning_rate": 6.632050516787719e-05,
1326
+ "loss": 0.5036,
1327
+ "memory/device_reserved (GiB)": 139.06,
1328
+ "memory/max_active (GiB)": 25.53,
1329
+ "memory/max_allocated (GiB)": 25.53,
1330
+ "ppl": 1.6547,
1331
+ "step": 2475,
1332
+ "tokens_per_second_per_gpu": 4256.1,
1333
+ "total_tokens": 47941250
1334
+ },
1335
+ {
1336
+ "epoch": 1.8754688672168043,
1337
+ "grad_norm": 0.21025419235229492,
1338
+ "learning_rate": 6.442934134345871e-05,
1339
+ "loss": 0.5019,
1340
+ "memory/device_reserved (GiB)": 139.06,
1341
+ "memory/max_active (GiB)": 25.53,
1342
+ "memory/max_allocated (GiB)": 25.53,
1343
+ "ppl": 1.6519,
1344
+ "step": 2500,
1345
+ "tokens_per_second_per_gpu": 3728.09,
1346
+ "total_tokens": 48383306
1347
+ },
1348
+ {
1349
+ "epoch": 1.8942235558889724,
1350
+ "grad_norm": 0.20130059123039246,
1351
+ "learning_rate": 6.255263255131172e-05,
1352
+ "loss": 0.5022,
1353
+ "memory/device_reserved (GiB)": 139.06,
1354
+ "memory/max_active (GiB)": 25.53,
1355
+ "memory/max_allocated (GiB)": 25.53,
1356
+ "ppl": 1.6524,
1357
+ "step": 2525,
1358
+ "tokens_per_second_per_gpu": 4178.95,
1359
+ "total_tokens": 48821862
1360
+ },
1361
+ {
1362
+ "epoch": 1.9129782445611403,
1363
+ "grad_norm": 0.19601669907569885,
1364
+ "learning_rate": 6.0691141439280785e-05,
1365
+ "loss": 0.4876,
1366
+ "memory/device_reserved (GiB)": 139.06,
1367
+ "memory/max_active (GiB)": 25.53,
1368
+ "memory/max_allocated (GiB)": 25.53,
1369
+ "ppl": 1.6284,
1370
+ "step": 2550,
1371
+ "tokens_per_second_per_gpu": 3998.52,
1372
+ "total_tokens": 49262344
1373
+ },
1374
+ {
1375
+ "epoch": 1.9317329332333082,
1376
+ "grad_norm": 0.20538586378097534,
1377
+ "learning_rate": 5.884562447112331e-05,
1378
+ "loss": 0.4796,
1379
+ "memory/device_reserved (GiB)": 139.06,
1380
+ "memory/max_active (GiB)": 25.53,
1381
+ "memory/max_allocated (GiB)": 25.53,
1382
+ "ppl": 1.6154,
1383
+ "step": 2575,
1384
+ "tokens_per_second_per_gpu": 4192.8,
1385
+ "total_tokens": 49702209
1386
+ },
1387
+ {
1388
+ "epoch": 1.9504876219054763,
1389
+ "grad_norm": 0.19957959651947021,
1390
+ "learning_rate": 5.701683161910115e-05,
1391
+ "loss": 0.5017,
1392
+ "memory/device_reserved (GiB)": 139.06,
1393
+ "memory/max_active (GiB)": 25.53,
1394
+ "memory/max_allocated (GiB)": 25.53,
1395
+ "ppl": 1.6515,
1396
+ "step": 2600,
1397
+ "tokens_per_second_per_gpu": 4244.94,
1398
+ "total_tokens": 50147673
1399
+ },
1400
+ {
1401
+ "epoch": 1.9692423105776444,
1402
+ "grad_norm": 0.20284536480903625,
1403
+ "learning_rate": 5.520550605921091e-05,
1404
+ "loss": 0.5024,
1405
+ "memory/device_reserved (GiB)": 139.06,
1406
+ "memory/max_active (GiB)": 25.53,
1407
+ "memory/max_allocated (GiB)": 25.53,
1408
+ "ppl": 1.6527,
1409
+ "step": 2625,
1410
+ "tokens_per_second_per_gpu": 4205.45,
1411
+ "total_tokens": 50589478
1412
+ },
1413
+ {
1414
+ "epoch": 1.9879969992498125,
1415
+ "grad_norm": 0.2044789344072342,
1416
+ "learning_rate": 5.34123838691753e-05,
1417
+ "loss": 0.4967,
1418
+ "memory/device_reserved (GiB)": 139.06,
1419
+ "memory/max_active (GiB)": 25.53,
1420
+ "memory/max_allocated (GiB)": 25.53,
1421
+ "ppl": 1.6433,
1422
+ "step": 2650,
1423
+ "tokens_per_second_per_gpu": 4204.9,
1424
+ "total_tokens": 51027800
1425
+ },
1426
+ {
1427
+ "epoch": 2.0067516879219807,
1428
+ "grad_norm": 0.2125943899154663,
1429
+ "learning_rate": 5.163819372931979e-05,
1430
+ "loss": 0.4862,
1431
+ "memory/device_reserved (GiB)": 139.06,
1432
+ "memory/max_active (GiB)": 25.53,
1433
+ "memory/max_allocated (GiB)": 25.53,
1434
+ "ppl": 1.6261,
1435
+ "step": 2675,
1436
+ "tokens_per_second_per_gpu": 3745.54,
1437
+ "total_tokens": 51469941
1438
+ },
1439
+ {
1440
+ "epoch": 2.0255063765941483,
1441
+ "grad_norm": 0.2312517911195755,
1442
+ "learning_rate": 4.9883656626454724e-05,
1443
+ "loss": 0.4782,
1444
+ "memory/device_reserved (GiB)": 139.06,
1445
+ "memory/max_active (GiB)": 25.53,
1446
+ "memory/max_allocated (GiB)": 25.53,
1447
+ "ppl": 1.6132,
1448
+ "step": 2700,
1449
+ "tokens_per_second_per_gpu": 4275.5,
1450
+ "total_tokens": 51921057
1451
+ },
1452
+ {
1453
+ "epoch": 2.0442610652663165,
1454
+ "grad_norm": 0.19745635986328125,
1455
+ "learning_rate": 4.81494855608843e-05,
1456
+ "loss": 0.4717,
1457
+ "memory/device_reserved (GiB)": 139.06,
1458
+ "memory/max_active (GiB)": 25.53,
1459
+ "memory/max_allocated (GiB)": 25.53,
1460
+ "ppl": 1.6027,
1461
+ "step": 2725,
1462
+ "tokens_per_second_per_gpu": 4290.88,
1463
+ "total_tokens": 52372623
1464
+ },
1465
+ {
1466
+ "epoch": 2.0630157539384846,
1467
+ "grad_norm": 0.22817276418209076,
1468
+ "learning_rate": 4.643638525666095e-05,
1469
+ "loss": 0.4817,
1470
+ "memory/device_reserved (GiB)": 139.06,
1471
+ "memory/max_active (GiB)": 25.53,
1472
+ "memory/max_allocated (GiB)": 25.53,
1473
+ "ppl": 1.6188,
1474
+ "step": 2750,
1475
+ "tokens_per_second_per_gpu": 4292.31,
1476
+ "total_tokens": 52823263
1477
+ },
1478
+ {
1479
+ "epoch": 2.0817704426106527,
1480
+ "grad_norm": 0.20878754556179047,
1481
+ "learning_rate": 4.4745051875203134e-05,
1482
+ "loss": 0.4774,
1483
+ "memory/device_reserved (GiB)": 139.06,
1484
+ "memory/max_active (GiB)": 25.53,
1485
+ "memory/max_allocated (GiB)": 25.53,
1486
+ "ppl": 1.6119,
1487
+ "step": 2775,
1488
+ "tokens_per_second_per_gpu": 4287.12,
1489
+ "total_tokens": 53272669
1490
+ },
1491
+ {
1492
+ "epoch": 2.100525131282821,
1493
+ "grad_norm": 0.18676196038722992,
1494
+ "learning_rate": 4.307617273239226e-05,
1495
+ "loss": 0.4824,
1496
+ "memory/device_reserved (GiB)": 139.06,
1497
+ "memory/max_active (GiB)": 25.53,
1498
+ "memory/max_allocated (GiB)": 25.53,
1499
+ "ppl": 1.62,
1500
+ "step": 2800,
1501
+ "tokens_per_second_per_gpu": 4304.14,
1502
+ "total_tokens": 53724750
1503
+ },
1504
+ {
1505
+ "epoch": 2.119279819954989,
1506
+ "grad_norm": 0.20670537650585175,
1507
+ "learning_rate": 4.1430426019264924e-05,
1508
+ "loss": 0.4701,
1509
+ "memory/device_reserved (GiB)": 139.06,
1510
+ "memory/max_active (GiB)": 25.53,
1511
+ "memory/max_allocated (GiB)": 25.53,
1512
+ "ppl": 1.6002,
1513
+ "step": 2825,
1514
+ "tokens_per_second_per_gpu": 4283.76,
1515
+ "total_tokens": 54172957
1516
+ },
1517
+ {
1518
+ "epoch": 2.1380345086271566,
1519
+ "grad_norm": 0.21445906162261963,
1520
+ "learning_rate": 3.980848052641286e-05,
1521
+ "loss": 0.4772,
1522
+ "memory/device_reserved (GiB)": 139.06,
1523
+ "memory/max_active (GiB)": 25.53,
1524
+ "memory/max_allocated (GiB)": 25.53,
1525
+ "ppl": 1.6116,
1526
+ "step": 2850,
1527
+ "tokens_per_second_per_gpu": 3768.93,
1528
+ "total_tokens": 54625827
1529
+ },
1530
+ {
1531
+ "epoch": 2.1567891972993247,
1532
+ "grad_norm": 0.21021129190921783,
1533
+ "learning_rate": 3.8210995372202896e-05,
1534
+ "loss": 0.471,
1535
+ "memory/device_reserved (GiB)": 139.06,
1536
+ "memory/max_active (GiB)": 25.53,
1537
+ "memory/max_allocated (GiB)": 25.53,
1538
+ "ppl": 1.6016,
1539
+ "step": 2875,
1540
+ "tokens_per_second_per_gpu": 4286.55,
1541
+ "total_tokens": 55076031
1542
+ },
1543
+ {
1544
+ "epoch": 2.175543885971493,
1545
+ "grad_norm": 0.23069453239440918,
1546
+ "learning_rate": 3.663861973492776e-05,
1547
+ "loss": 0.4722,
1548
+ "memory/device_reserved (GiB)": 139.06,
1549
+ "memory/max_active (GiB)": 25.53,
1550
+ "memory/max_allocated (GiB)": 25.53,
1551
+ "ppl": 1.6035,
1552
+ "step": 2900,
1553
+ "tokens_per_second_per_gpu": 4291.53,
1554
+ "total_tokens": 55527864
1555
+ },
1556
+ {
1557
+ "epoch": 2.194298574643661,
1558
+ "grad_norm": 0.22328485548496246,
1559
+ "learning_rate": 3.509199258899603e-05,
1560
+ "loss": 0.474,
1561
+ "memory/device_reserved (GiB)": 139.06,
1562
+ "memory/max_active (GiB)": 25.53,
1563
+ "memory/max_allocated (GiB)": 25.53,
1564
+ "ppl": 1.6064,
1565
+ "step": 2925,
1566
+ "tokens_per_second_per_gpu": 4262.17,
1567
+ "total_tokens": 55976245
1568
+ },
1569
+ {
1570
+ "epoch": 2.213053263315829,
1571
+ "grad_norm": 0.20422938466072083,
1572
+ "learning_rate": 3.3571742445268995e-05,
1573
+ "loss": 0.4721,
1574
+ "memory/device_reserved (GiB)": 139.06,
1575
+ "memory/max_active (GiB)": 25.53,
1576
+ "memory/max_allocated (GiB)": 25.53,
1577
+ "ppl": 1.6034,
1578
+ "step": 2950,
1579
+ "tokens_per_second_per_gpu": 4339.03,
1580
+ "total_tokens": 56430293
1581
+ },
1582
+ {
1583
+ "epoch": 2.231807951987997,
1584
+ "grad_norm": 0.21462033689022064,
1585
+ "learning_rate": 3.2078487095649236e-05,
1586
+ "loss": 0.4798,
1587
+ "memory/device_reserved (GiB)": 139.06,
1588
+ "memory/max_active (GiB)": 25.53,
1589
+ "memory/max_allocated (GiB)": 25.53,
1590
+ "ppl": 1.6158,
1591
+ "step": 2975,
1592
+ "tokens_per_second_per_gpu": 4274.93,
1593
+ "total_tokens": 56879796
1594
+ },
1595
+ {
1596
+ "epoch": 2.250562640660165,
1597
+ "grad_norm": 0.21800526976585388,
1598
+ "learning_rate": 3.061283336202545e-05,
1599
+ "loss": 0.4733,
1600
+ "memory/device_reserved (GiB)": 139.06,
1601
+ "memory/max_active (GiB)": 25.53,
1602
+ "memory/max_allocated (GiB)": 25.53,
1603
+ "ppl": 1.6053,
1604
+ "step": 3000,
1605
+ "tokens_per_second_per_gpu": 4290.7,
1606
+ "total_tokens": 57329902
1607
+ },
1608
+ {
1609
+ "epoch": 2.250562640660165,
1610
+ "eval_loss": 0.49272674322128296,
1611
+ "eval_ppl": 1.6368,
1612
+ "eval_runtime": 139.4189,
1613
+ "eval_samples_per_second": 5.236,
1614
+ "eval_steps_per_second": 1.047,
1615
+ "memory/device_reserved (GiB)": 139.06,
1616
+ "memory/max_active (GiB)": 19.1,
1617
+ "memory/max_allocated (GiB)": 19.1,
1618
+ "step": 3000
1619
+ }
1620
+ ],
1621
+ "logging_steps": 25,
1622
+ "max_steps": 3996,
1623
+ "num_input_tokens_seen": 0,
1624
+ "num_train_epochs": 3,
1625
+ "save_steps": 1000,
1626
+ "stateful_callbacks": {
1627
+ "TrainerControl": {
1628
+ "args": {
1629
+ "should_epoch_stop": false,
1630
+ "should_evaluate": false,
1631
+ "should_log": false,
1632
+ "should_save": true,
1633
+ "should_training_stop": false
1634
+ },
1635
+ "attributes": {}
1636
+ }
1637
+ },
1638
+ "total_flos": 2.44194006269952e+18,
1639
+ "train_batch_size": 5,
1640
+ "trial_name": null,
1641
+ "trial_params": null
1642
+ }
checkpoint-3000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a75cafa9afe18e1aa48e766453f03add03ceb5dd78011703e6068968ae04eab2
3
+ size 7761
checkpoint-3996/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: codellama/CodeLlama-7b-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:codellama/CodeLlama-7b-hf
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- 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. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ 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).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.18.0
checkpoint-3996/adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "codellama/CodeLlama-7b-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
9
+ "ensure_weight_tying": false,
10
+ "eva_config": null,
11
+ "exclude_modules": null,
12
+ "fan_in_fan_out": null,
13
+ "inference_mode": true,
14
+ "init_lora_weights": true,
15
+ "layer_replication": null,
16
+ "layers_pattern": null,
17
+ "layers_to_transform": null,
18
+ "loftq_config": {},
19
+ "lora_alpha": 32,
20
+ "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
+ "megatron_config": null,
23
+ "megatron_core": "megatron.core",
24
+ "modules_to_save": null,
25
+ "peft_type": "LORA",
26
+ "peft_version": "0.18.0",
27
+ "qalora_group_size": 16,
28
+ "r": 16,
29
+ "rank_pattern": {},
30
+ "revision": null,
31
+ "target_modules": [
32
+ "o_proj",
33
+ "v_proj",
34
+ "k_proj",
35
+ "q_proj"
36
+ ],
37
+ "target_parameters": [],
38
+ "task_type": "CAUSAL_LM",
39
+ "trainable_token_indices": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
checkpoint-3996/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:117f1345e5c50f25128a7a46faf63217f9c93561ea40a0465fc49fe91eab762a
3
+ size 67143296
checkpoint-3996/chat_template.jinja ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
2
+
3
+ '+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
4
+
5
+ ' }}{% endif %}
checkpoint-3996/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:58aad3dbb3cfe1b98763989bd9c75ff86952302613d5f2ee49aab4c7295f5add
3
+ size 134433995
checkpoint-3996/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b04604ef23b357ed9d36f23ae035970360a95042e84454038a4f247858716bb3
3
+ size 14645
checkpoint-3996/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:02ee8d28df036529f2e1f752f7ac7ca36c848af464c831112a3b6510f5494afb
3
+ size 1465
checkpoint-3996/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-3996/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
3
+ size 500058
checkpoint-3996/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": true,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "extra_special_tokens": {},
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false,
43
+ "use_fast": true
44
+ }
checkpoint-3996/trainer_state.json ADDED
@@ -0,0 +1,2149 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 2.9977494373593396,
6
+ "eval_steps": 1000,
7
+ "global_step": 3996,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0,
14
+ "eval_loss": 1.6887853145599365,
15
+ "eval_ppl": 5.4129,
16
+ "eval_runtime": 167.3526,
17
+ "eval_samples_per_second": 4.362,
18
+ "eval_steps_per_second": 0.872,
19
+ "memory/device_reserved (GiB)": 139.12,
20
+ "memory/max_active (GiB)": 18.94,
21
+ "memory/max_allocated (GiB)": 18.94,
22
+ "step": 0
23
+ },
24
+ {
25
+ "epoch": 0.018754688672168042,
26
+ "grad_norm": 1.415561556816101,
27
+ "learning_rate": 4.8e-05,
28
+ "loss": 1.6848,
29
+ "memory/device_reserved (GiB)": 139.11,
30
+ "memory/max_active (GiB)": 25.53,
31
+ "memory/max_allocated (GiB)": 25.53,
32
+ "ppl": 5.3914,
33
+ "step": 25,
34
+ "tokens_per_second_per_gpu": 16277.76,
35
+ "total_tokens": 1723633
36
+ },
37
+ {
38
+ "epoch": 0.037509377344336084,
39
+ "grad_norm": 0.33179354667663574,
40
+ "learning_rate": 9.8e-05,
41
+ "loss": 0.9839,
42
+ "memory/device_reserved (GiB)": 139.06,
43
+ "memory/max_active (GiB)": 25.53,
44
+ "memory/max_allocated (GiB)": 25.53,
45
+ "ppl": 2.6749,
46
+ "step": 50,
47
+ "tokens_per_second_per_gpu": 4303.21,
48
+ "total_tokens": 2175386
49
+ },
50
+ {
51
+ "epoch": 0.056264066016504126,
52
+ "grad_norm": 0.17453454434871674,
53
+ "learning_rate": 0.000148,
54
+ "loss": 0.8002,
55
+ "memory/device_reserved (GiB)": 139.06,
56
+ "memory/max_active (GiB)": 25.53,
57
+ "memory/max_allocated (GiB)": 25.53,
58
+ "ppl": 2.226,
59
+ "step": 75,
60
+ "tokens_per_second_per_gpu": 3776.03,
61
+ "total_tokens": 2623712
62
+ },
63
+ {
64
+ "epoch": 0.07501875468867217,
65
+ "grad_norm": 0.19318008422851562,
66
+ "learning_rate": 0.00019800000000000002,
67
+ "loss": 0.7218,
68
+ "memory/device_reserved (GiB)": 139.06,
69
+ "memory/max_active (GiB)": 25.53,
70
+ "memory/max_allocated (GiB)": 25.53,
71
+ "ppl": 2.0581,
72
+ "step": 100,
73
+ "tokens_per_second_per_gpu": 4252.49,
74
+ "total_tokens": 3072519
75
+ },
76
+ {
77
+ "epoch": 0.09377344336084022,
78
+ "grad_norm": 0.18435686826705933,
79
+ "learning_rate": 0.00019998127418269004,
80
+ "loss": 0.6759,
81
+ "memory/device_reserved (GiB)": 139.06,
82
+ "memory/max_active (GiB)": 25.53,
83
+ "memory/max_allocated (GiB)": 25.53,
84
+ "ppl": 1.9658,
85
+ "step": 125,
86
+ "tokens_per_second_per_gpu": 4303.31,
87
+ "total_tokens": 3523983
88
+ },
89
+ {
90
+ "epoch": 0.11252813203300825,
91
+ "grad_norm": 0.19870473444461823,
92
+ "learning_rate": 0.00019992195096972548,
93
+ "loss": 0.6703,
94
+ "memory/device_reserved (GiB)": 139.06,
95
+ "memory/max_active (GiB)": 25.53,
96
+ "memory/max_allocated (GiB)": 25.53,
97
+ "ppl": 1.9548,
98
+ "step": 150,
99
+ "tokens_per_second_per_gpu": 4260.86,
100
+ "total_tokens": 3973452
101
+ },
102
+ {
103
+ "epoch": 0.1312828207051763,
104
+ "grad_norm": 0.20499658584594727,
105
+ "learning_rate": 0.0001998220219574743,
106
+ "loss": 0.6381,
107
+ "memory/device_reserved (GiB)": 139.06,
108
+ "memory/max_active (GiB)": 25.53,
109
+ "memory/max_allocated (GiB)": 25.53,
110
+ "ppl": 1.8929,
111
+ "step": 175,
112
+ "tokens_per_second_per_gpu": 4288.64,
113
+ "total_tokens": 4423763
114
+ },
115
+ {
116
+ "epoch": 0.15003750937734434,
117
+ "grad_norm": 0.18934418261051178,
118
+ "learning_rate": 0.00019968152775460537,
119
+ "loss": 0.6383,
120
+ "memory/device_reserved (GiB)": 139.06,
121
+ "memory/max_active (GiB)": 25.53,
122
+ "memory/max_allocated (GiB)": 25.53,
123
+ "ppl": 1.8933,
124
+ "step": 200,
125
+ "tokens_per_second_per_gpu": 4244.79,
126
+ "total_tokens": 4872365
127
+ },
128
+ {
129
+ "epoch": 0.16879219804951237,
130
+ "grad_norm": 0.1827855408191681,
131
+ "learning_rate": 0.00019950052545447352,
132
+ "loss": 0.6347,
133
+ "memory/device_reserved (GiB)": 139.06,
134
+ "memory/max_active (GiB)": 25.53,
135
+ "memory/max_allocated (GiB)": 25.53,
136
+ "ppl": 1.8865,
137
+ "step": 225,
138
+ "tokens_per_second_per_gpu": 4252.71,
139
+ "total_tokens": 5319322
140
+ },
141
+ {
142
+ "epoch": 0.18754688672168043,
143
+ "grad_norm": 0.16483066976070404,
144
+ "learning_rate": 0.00019927908861191827,
145
+ "loss": 0.6392,
146
+ "memory/device_reserved (GiB)": 139.06,
147
+ "memory/max_active (GiB)": 25.53,
148
+ "memory/max_allocated (GiB)": 25.53,
149
+ "ppl": 1.895,
150
+ "step": 250,
151
+ "tokens_per_second_per_gpu": 3772.0,
152
+ "total_tokens": 5768644
153
+ },
154
+ {
155
+ "epoch": 0.20630157539384847,
156
+ "grad_norm": 0.17186357080936432,
157
+ "learning_rate": 0.00019901730721337302,
158
+ "loss": 0.614,
159
+ "memory/device_reserved (GiB)": 139.06,
160
+ "memory/max_active (GiB)": 25.53,
161
+ "memory/max_allocated (GiB)": 25.53,
162
+ "ppl": 1.8478,
163
+ "step": 275,
164
+ "tokens_per_second_per_gpu": 4281.82,
165
+ "total_tokens": 6220751
166
+ },
167
+ {
168
+ "epoch": 0.2250562640660165,
169
+ "grad_norm": 0.18073013424873352,
170
+ "learning_rate": 0.00019871528764029667,
171
+ "loss": 0.6196,
172
+ "memory/device_reserved (GiB)": 139.06,
173
+ "memory/max_active (GiB)": 25.53,
174
+ "memory/max_allocated (GiB)": 25.53,
175
+ "ppl": 1.8582,
176
+ "step": 300,
177
+ "tokens_per_second_per_gpu": 4234.51,
178
+ "total_tokens": 6668111
179
+ },
180
+ {
181
+ "epoch": 0.24381095273818454,
182
+ "grad_norm": 0.19639697670936584,
183
+ "learning_rate": 0.00019837315262594306,
184
+ "loss": 0.6181,
185
+ "memory/device_reserved (GiB)": 139.06,
186
+ "memory/max_active (GiB)": 25.53,
187
+ "memory/max_allocated (GiB)": 25.53,
188
+ "ppl": 1.8554,
189
+ "step": 325,
190
+ "tokens_per_second_per_gpu": 4261.44,
191
+ "total_tokens": 7117439
192
+ },
193
+ {
194
+ "epoch": 0.2625656414103526,
195
+ "grad_norm": 0.1670486479997635,
196
+ "learning_rate": 0.00019799104120548492,
197
+ "loss": 0.6141,
198
+ "memory/device_reserved (GiB)": 139.06,
199
+ "memory/max_active (GiB)": 25.53,
200
+ "memory/max_allocated (GiB)": 25.53,
201
+ "ppl": 1.848,
202
+ "step": 350,
203
+ "tokens_per_second_per_gpu": 4298.97,
204
+ "total_tokens": 7569060
205
+ },
206
+ {
207
+ "epoch": 0.2813203300825206,
208
+ "grad_norm": 0.17752495408058167,
209
+ "learning_rate": 0.00019756910865951377,
210
+ "loss": 0.6075,
211
+ "memory/device_reserved (GiB)": 139.06,
212
+ "memory/max_active (GiB)": 25.53,
213
+ "memory/max_allocated (GiB)": 25.53,
214
+ "ppl": 1.8358,
215
+ "step": 375,
216
+ "tokens_per_second_per_gpu": 4256.6,
217
+ "total_tokens": 8017630
218
+ },
219
+ {
220
+ "epoch": 0.30007501875468867,
221
+ "grad_norm": 0.2000180035829544,
222
+ "learning_rate": 0.00019710752645093747,
223
+ "loss": 0.6108,
224
+ "memory/device_reserved (GiB)": 139.06,
225
+ "memory/max_active (GiB)": 25.53,
226
+ "memory/max_allocated (GiB)": 25.53,
227
+ "ppl": 1.8419,
228
+ "step": 400,
229
+ "tokens_per_second_per_gpu": 4245.46,
230
+ "total_tokens": 8464998
231
+ },
232
+ {
233
+ "epoch": 0.31882970742685673,
234
+ "grad_norm": 0.17395919561386108,
235
+ "learning_rate": 0.00019660648215530206,
236
+ "loss": 0.5966,
237
+ "memory/device_reserved (GiB)": 139.06,
238
+ "memory/max_active (GiB)": 25.53,
239
+ "memory/max_allocated (GiB)": 25.53,
240
+ "ppl": 1.8159,
241
+ "step": 425,
242
+ "tokens_per_second_per_gpu": 3758.92,
243
+ "total_tokens": 8914723
244
+ },
245
+ {
246
+ "epoch": 0.33758439609902474,
247
+ "grad_norm": 0.18785236775875092,
248
+ "learning_rate": 0.00019606617938456572,
249
+ "loss": 0.6099,
250
+ "memory/device_reserved (GiB)": 139.06,
251
+ "memory/max_active (GiB)": 25.53,
252
+ "memory/max_allocated (GiB)": 25.53,
253
+ "ppl": 1.8402,
254
+ "step": 450,
255
+ "tokens_per_second_per_gpu": 4200.53,
256
+ "total_tokens": 9359638
257
+ },
258
+ {
259
+ "epoch": 0.3563390847711928,
260
+ "grad_norm": 0.17702797055244446,
261
+ "learning_rate": 0.0001954868377043559,
262
+ "loss": 0.5922,
263
+ "memory/device_reserved (GiB)": 139.06,
264
+ "memory/max_active (GiB)": 25.53,
265
+ "memory/max_allocated (GiB)": 25.53,
266
+ "ppl": 1.808,
267
+ "step": 475,
268
+ "tokens_per_second_per_gpu": 4265.36,
269
+ "total_tokens": 9810837
270
+ },
271
+ {
272
+ "epoch": 0.37509377344336087,
273
+ "grad_norm": 0.19927558302879333,
274
+ "learning_rate": 0.00019486869254474337,
275
+ "loss": 0.5759,
276
+ "memory/device_reserved (GiB)": 139.06,
277
+ "memory/max_active (GiB)": 25.53,
278
+ "memory/max_allocated (GiB)": 25.53,
279
+ "ppl": 1.7787,
280
+ "step": 500,
281
+ "tokens_per_second_per_gpu": 4276.25,
282
+ "total_tokens": 10261446
283
+ },
284
+ {
285
+ "epoch": 0.3938484621155289,
286
+ "grad_norm": 0.1908370852470398,
287
+ "learning_rate": 0.0001942119951045692,
288
+ "loss": 0.584,
289
+ "memory/device_reserved (GiB)": 139.06,
290
+ "memory/max_active (GiB)": 25.53,
291
+ "memory/max_allocated (GiB)": 25.53,
292
+ "ppl": 1.7932,
293
+ "step": 525,
294
+ "tokens_per_second_per_gpu": 4272.28,
295
+ "total_tokens": 10707841
296
+ },
297
+ {
298
+ "epoch": 0.41260315078769694,
299
+ "grad_norm": 0.2064146101474762,
300
+ "learning_rate": 0.00019351701224936383,
301
+ "loss": 0.5791,
302
+ "memory/device_reserved (GiB)": 139.06,
303
+ "memory/max_active (GiB)": 25.53,
304
+ "memory/max_allocated (GiB)": 25.53,
305
+ "ppl": 1.7844,
306
+ "step": 550,
307
+ "tokens_per_second_per_gpu": 4250.37,
308
+ "total_tokens": 11155384
309
+ },
310
+ {
311
+ "epoch": 0.43135783945986494,
312
+ "grad_norm": 0.26748332381248474,
313
+ "learning_rate": 0.0001927840264028995,
314
+ "loss": 0.5758,
315
+ "memory/device_reserved (GiB)": 139.06,
316
+ "memory/max_active (GiB)": 25.53,
317
+ "memory/max_allocated (GiB)": 25.53,
318
+ "ppl": 1.7786,
319
+ "step": 575,
320
+ "tokens_per_second_per_gpu": 4256.55,
321
+ "total_tokens": 11601192
322
+ },
323
+ {
324
+ "epoch": 0.450112528132033,
325
+ "grad_norm": 0.17514832317829132,
326
+ "learning_rate": 0.00019201333543242036,
327
+ "loss": 0.5791,
328
+ "memory/device_reserved (GiB)": 139.06,
329
+ "memory/max_active (GiB)": 25.53,
330
+ "memory/max_allocated (GiB)": 25.53,
331
+ "ppl": 1.7844,
332
+ "step": 600,
333
+ "tokens_per_second_per_gpu": 3770.83,
334
+ "total_tokens": 12048477
335
+ },
336
+ {
337
+ "epoch": 0.46886721680420107,
338
+ "grad_norm": 0.22069169580936432,
339
+ "learning_rate": 0.00019120525252759647,
340
+ "loss": 0.5803,
341
+ "memory/device_reserved (GiB)": 139.06,
342
+ "memory/max_active (GiB)": 25.53,
343
+ "memory/max_allocated (GiB)": 25.53,
344
+ "ppl": 1.7866,
345
+ "step": 625,
346
+ "tokens_per_second_per_gpu": 4179.31,
347
+ "total_tokens": 12488141
348
+ },
349
+ {
350
+ "epoch": 0.4876219054763691,
351
+ "grad_norm": 0.20555566251277924,
352
+ "learning_rate": 0.00019036010607325138,
353
+ "loss": 0.5716,
354
+ "memory/device_reserved (GiB)": 139.06,
355
+ "memory/max_active (GiB)": 25.53,
356
+ "memory/max_allocated (GiB)": 25.53,
357
+ "ppl": 1.7711,
358
+ "step": 650,
359
+ "tokens_per_second_per_gpu": 4209.96,
360
+ "total_tokens": 12934358
361
+ },
362
+ {
363
+ "epoch": 0.5063765941485371,
364
+ "grad_norm": 0.19018156826496124,
365
+ "learning_rate": 0.00018947823951591478,
366
+ "loss": 0.5608,
367
+ "memory/device_reserved (GiB)": 139.06,
368
+ "memory/max_active (GiB)": 25.53,
369
+ "memory/max_allocated (GiB)": 25.53,
370
+ "ppl": 1.7521,
371
+ "step": 675,
372
+ "tokens_per_second_per_gpu": 4226.4,
373
+ "total_tokens": 13378983
374
+ },
375
+ {
376
+ "epoch": 0.5251312828207052,
377
+ "grad_norm": 0.17173859477043152,
378
+ "learning_rate": 0.00018856001122425416,
379
+ "loss": 0.5667,
380
+ "memory/device_reserved (GiB)": 139.06,
381
+ "memory/max_active (GiB)": 25.53,
382
+ "memory/max_allocated (GiB)": 25.53,
383
+ "ppl": 1.7624,
384
+ "step": 700,
385
+ "tokens_per_second_per_gpu": 4265.57,
386
+ "total_tokens": 13829519
387
+ },
388
+ {
389
+ "epoch": 0.5438859714928732,
390
+ "grad_norm": 0.17706550657749176,
391
+ "learning_rate": 0.0001876057943434428,
392
+ "loss": 0.565,
393
+ "memory/device_reserved (GiB)": 139.06,
394
+ "memory/max_active (GiB)": 25.53,
395
+ "memory/max_allocated (GiB)": 25.53,
396
+ "ppl": 1.7594,
397
+ "step": 725,
398
+ "tokens_per_second_per_gpu": 4281.61,
399
+ "total_tokens": 14281879
400
+ },
401
+ {
402
+ "epoch": 0.5626406601650412,
403
+ "grad_norm": 0.18528586626052856,
404
+ "learning_rate": 0.00018661597664352284,
405
+ "loss": 0.5666,
406
+ "memory/device_reserved (GiB)": 139.06,
407
+ "memory/max_active (GiB)": 25.53,
408
+ "memory/max_allocated (GiB)": 25.53,
409
+ "ppl": 1.7623,
410
+ "step": 750,
411
+ "tokens_per_second_per_gpu": 4229.32,
412
+ "total_tokens": 14725919
413
+ },
414
+ {
415
+ "epoch": 0.5813953488372093,
416
+ "grad_norm": 0.16790929436683655,
417
+ "learning_rate": 0.00018559096036182516,
418
+ "loss": 0.5633,
419
+ "memory/device_reserved (GiB)": 139.06,
420
+ "memory/max_active (GiB)": 25.53,
421
+ "memory/max_allocated (GiB)": 25.53,
422
+ "ppl": 1.7565,
423
+ "step": 775,
424
+ "tokens_per_second_per_gpu": 3775.0,
425
+ "total_tokens": 15175146
426
+ },
427
+ {
428
+ "epoch": 0.6001500375093773,
429
+ "grad_norm": 0.17511805891990662,
430
+ "learning_rate": 0.00018453116203951005,
431
+ "loss": 0.5664,
432
+ "memory/device_reserved (GiB)": 139.06,
433
+ "memory/max_active (GiB)": 25.53,
434
+ "memory/max_allocated (GiB)": 25.53,
435
+ "ppl": 1.7619,
436
+ "step": 800,
437
+ "tokens_per_second_per_gpu": 4218.07,
438
+ "total_tokens": 15619901
439
+ },
440
+ {
441
+ "epoch": 0.6189047261815454,
442
+ "grad_norm": 0.19853387773036957,
443
+ "learning_rate": 0.0001834370123522954,
444
+ "loss": 0.5646,
445
+ "memory/device_reserved (GiB)": 139.06,
446
+ "memory/max_active (GiB)": 25.53,
447
+ "memory/max_allocated (GiB)": 25.53,
448
+ "ppl": 1.7587,
449
+ "step": 825,
450
+ "tokens_per_second_per_gpu": 4230.84,
451
+ "total_tokens": 16066102
452
+ },
453
+ {
454
+ "epoch": 0.6376594148537135,
455
+ "grad_norm": 0.18872258067131042,
456
+ "learning_rate": 0.00018230895593544056,
457
+ "loss": 0.552,
458
+ "memory/device_reserved (GiB)": 139.06,
459
+ "memory/max_active (GiB)": 25.53,
460
+ "memory/max_allocated (GiB)": 25.53,
461
+ "ppl": 1.7367,
462
+ "step": 850,
463
+ "tokens_per_second_per_gpu": 4222.33,
464
+ "total_tokens": 16510696
465
+ },
466
+ {
467
+ "epoch": 0.6564141035258815,
468
+ "grad_norm": 0.9702818989753723,
469
+ "learning_rate": 0.0001811474512030578,
470
+ "loss": 0.5607,
471
+ "memory/device_reserved (GiB)": 139.06,
472
+ "memory/max_active (GiB)": 25.53,
473
+ "memory/max_allocated (GiB)": 25.53,
474
+ "ppl": 1.7519,
475
+ "step": 875,
476
+ "tokens_per_second_per_gpu": 4200.39,
477
+ "total_tokens": 16953918
478
+ },
479
+ {
480
+ "epoch": 0.6751687921980495,
481
+ "grad_norm": 0.17479568719863892,
482
+ "learning_rate": 0.00017995297016182405,
483
+ "loss": 0.564,
484
+ "memory/device_reserved (GiB)": 139.06,
485
+ "memory/max_active (GiB)": 25.53,
486
+ "memory/max_allocated (GiB)": 25.53,
487
+ "ppl": 1.7577,
488
+ "step": 900,
489
+ "tokens_per_second_per_gpu": 4210.15,
490
+ "total_tokens": 17396453
491
+ },
492
+ {
493
+ "epoch": 0.6939234808702176,
494
+ "grad_norm": 0.1948954463005066,
495
+ "learning_rate": 0.0001787259982191692,
496
+ "loss": 0.5511,
497
+ "memory/device_reserved (GiB)": 139.06,
498
+ "memory/max_active (GiB)": 25.53,
499
+ "memory/max_allocated (GiB)": 25.53,
500
+ "ppl": 1.7352,
501
+ "step": 925,
502
+ "tokens_per_second_per_gpu": 4237.98,
503
+ "total_tokens": 17841287
504
+ },
505
+ {
506
+ "epoch": 0.7126781695423856,
507
+ "grad_norm": 0.19541053473949432,
508
+ "learning_rate": 0.00017746703398601872,
509
+ "loss": 0.5532,
510
+ "memory/device_reserved (GiB)": 139.06,
511
+ "memory/max_active (GiB)": 25.53,
512
+ "memory/max_allocated (GiB)": 25.53,
513
+ "ppl": 1.7388,
514
+ "step": 950,
515
+ "tokens_per_second_per_gpu": 3725.33,
516
+ "total_tokens": 18283596
517
+ },
518
+ {
519
+ "epoch": 0.7314328582145536,
520
+ "grad_norm": 0.1818365603685379,
521
+ "learning_rate": 0.0001761765890741701,
522
+ "loss": 0.5521,
523
+ "memory/device_reserved (GiB)": 139.06,
524
+ "memory/max_active (GiB)": 25.53,
525
+ "memory/max_allocated (GiB)": 25.53,
526
+ "ppl": 1.7369,
527
+ "step": 975,
528
+ "tokens_per_second_per_gpu": 4211.63,
529
+ "total_tokens": 18726722
530
+ },
531
+ {
532
+ "epoch": 0.7501875468867217,
533
+ "grad_norm": 0.1838025599718094,
534
+ "learning_rate": 0.00017485518788838705,
535
+ "loss": 0.5511,
536
+ "memory/device_reserved (GiB)": 139.06,
537
+ "memory/max_active (GiB)": 25.53,
538
+ "memory/max_allocated (GiB)": 25.53,
539
+ "ppl": 1.7352,
540
+ "step": 1000,
541
+ "tokens_per_second_per_gpu": 3962.4,
542
+ "total_tokens": 19167258
543
+ },
544
+ {
545
+ "epoch": 0.7501875468867217,
546
+ "eval_loss": 0.540988564491272,
547
+ "eval_ppl": 1.7177,
548
+ "eval_runtime": 138.0264,
549
+ "eval_samples_per_second": 5.289,
550
+ "eval_steps_per_second": 1.058,
551
+ "memory/device_reserved (GiB)": 139.02,
552
+ "memory/max_active (GiB)": 19.1,
553
+ "memory/max_allocated (GiB)": 19.1,
554
+ "step": 1000
555
+ },
556
+ {
557
+ "epoch": 0.7689422355588897,
558
+ "grad_norm": 0.2199818342924118,
559
+ "learning_rate": 0.00017350336741329413,
560
+ "loss": 0.549,
561
+ "memory/device_reserved (GiB)": 139.06,
562
+ "memory/max_active (GiB)": 25.53,
563
+ "memory/max_allocated (GiB)": 25.53,
564
+ "ppl": 1.7315,
565
+ "step": 1025,
566
+ "tokens_per_second_per_gpu": 4129.73,
567
+ "total_tokens": 20870820
568
+ },
569
+ {
570
+ "epoch": 0.7876969242310577,
571
+ "grad_norm": 0.19783177971839905,
572
+ "learning_rate": 0.0001721216769951596,
573
+ "loss": 0.5615,
574
+ "memory/device_reserved (GiB)": 139.06,
575
+ "memory/max_active (GiB)": 25.53,
576
+ "memory/max_allocated (GiB)": 25.53,
577
+ "ppl": 1.7533,
578
+ "step": 1050,
579
+ "tokens_per_second_per_gpu": 4243.63,
580
+ "total_tokens": 21317982
581
+ },
582
+ {
583
+ "epoch": 0.8064516129032258,
584
+ "grad_norm": 0.1678430140018463,
585
+ "learning_rate": 0.00017071067811865476,
586
+ "loss": 0.5557,
587
+ "memory/device_reserved (GiB)": 139.06,
588
+ "memory/max_active (GiB)": 25.53,
589
+ "memory/max_allocated (GiB)": 25.53,
590
+ "ppl": 1.7432,
591
+ "step": 1075,
592
+ "tokens_per_second_per_gpu": 4092.04,
593
+ "total_tokens": 21754087
594
+ },
595
+ {
596
+ "epoch": 0.8252063015753939,
597
+ "grad_norm": 0.16523879766464233,
598
+ "learning_rate": 0.00016927094417868048,
599
+ "loss": 0.556,
600
+ "memory/device_reserved (GiB)": 139.06,
601
+ "memory/max_active (GiB)": 25.53,
602
+ "memory/max_allocated (GiB)": 25.53,
603
+ "ppl": 1.7437,
604
+ "step": 1100,
605
+ "tokens_per_second_per_gpu": 4187.02,
606
+ "total_tokens": 22198779
607
+ },
608
+ {
609
+ "epoch": 0.8439609902475619,
610
+ "grad_norm": 0.18177717924118042,
611
+ "learning_rate": 0.00016780306024735382,
612
+ "loss": 0.5468,
613
+ "memory/device_reserved (GiB)": 139.06,
614
+ "memory/max_active (GiB)": 25.53,
615
+ "memory/max_allocated (GiB)": 25.53,
616
+ "ppl": 1.7277,
617
+ "step": 1125,
618
+ "tokens_per_second_per_gpu": 4198.97,
619
+ "total_tokens": 22639769
620
+ },
621
+ {
622
+ "epoch": 0.8627156789197299,
623
+ "grad_norm": 0.17299720644950867,
624
+ "learning_rate": 0.0001663076228362492,
625
+ "loss": 0.554,
626
+ "memory/device_reserved (GiB)": 139.06,
627
+ "memory/max_active (GiB)": 25.53,
628
+ "memory/max_allocated (GiB)": 25.53,
629
+ "ppl": 1.7402,
630
+ "step": 1150,
631
+ "tokens_per_second_per_gpu": 3762.13,
632
+ "total_tokens": 23086742
633
+ },
634
+ {
635
+ "epoch": 0.881470367591898,
636
+ "grad_norm": 0.19112971425056458,
637
+ "learning_rate": 0.00016478523965399085,
638
+ "loss": 0.5434,
639
+ "memory/device_reserved (GiB)": 139.06,
640
+ "memory/max_active (GiB)": 25.53,
641
+ "memory/max_allocated (GiB)": 25.53,
642
+ "ppl": 1.7219,
643
+ "step": 1175,
644
+ "tokens_per_second_per_gpu": 4205.37,
645
+ "total_tokens": 23528106
646
+ },
647
+ {
648
+ "epoch": 0.900225056264066,
649
+ "grad_norm": 0.17930163443088531,
650
+ "learning_rate": 0.00016323652935929536,
651
+ "loss": 0.5362,
652
+ "memory/device_reserved (GiB)": 139.06,
653
+ "memory/max_active (GiB)": 25.53,
654
+ "memory/max_allocated (GiB)": 25.53,
655
+ "ppl": 1.7095,
656
+ "step": 1200,
657
+ "tokens_per_second_per_gpu": 4228.83,
658
+ "total_tokens": 23974427
659
+ },
660
+ {
661
+ "epoch": 0.918979744936234,
662
+ "grad_norm": 0.18718039989471436,
663
+ "learning_rate": 0.00016166212130956382,
664
+ "loss": 0.5533,
665
+ "memory/device_reserved (GiB)": 139.06,
666
+ "memory/max_active (GiB)": 25.53,
667
+ "memory/max_allocated (GiB)": 25.53,
668
+ "ppl": 1.739,
669
+ "step": 1225,
670
+ "tokens_per_second_per_gpu": 4211.64,
671
+ "total_tokens": 24415919
672
+ },
673
+ {
674
+ "epoch": 0.9377344336084021,
675
+ "grad_norm": 0.17105573415756226,
676
+ "learning_rate": 0.0001600626553051268,
677
+ "loss": 0.5492,
678
+ "memory/device_reserved (GiB)": 139.06,
679
+ "memory/max_active (GiB)": 25.53,
680
+ "memory/max_allocated (GiB)": 25.53,
681
+ "ppl": 1.7319,
682
+ "step": 1250,
683
+ "tokens_per_second_per_gpu": 4183.86,
684
+ "total_tokens": 24854345
685
+ },
686
+ {
687
+ "epoch": 0.9564891222805701,
688
+ "grad_norm": 0.1733955442905426,
689
+ "learning_rate": 0.0001584387813292454,
690
+ "loss": 0.5348,
691
+ "memory/device_reserved (GiB)": 139.06,
692
+ "memory/max_active (GiB)": 25.53,
693
+ "memory/max_allocated (GiB)": 25.53,
694
+ "ppl": 1.7071,
695
+ "step": 1275,
696
+ "tokens_per_second_per_gpu": 4172.93,
697
+ "total_tokens": 25292647
698
+ },
699
+ {
700
+ "epoch": 0.9752438109527382,
701
+ "grad_norm": 0.1858205944299698,
702
+ "learning_rate": 0.00015679115928397401,
703
+ "loss": 0.5527,
704
+ "memory/device_reserved (GiB)": 139.06,
705
+ "memory/max_active (GiB)": 25.53,
706
+ "memory/max_allocated (GiB)": 25.53,
707
+ "ppl": 1.7379,
708
+ "step": 1300,
709
+ "tokens_per_second_per_gpu": 4226.34,
710
+ "total_tokens": 25733591
711
+ },
712
+ {
713
+ "epoch": 0.9939984996249063,
714
+ "grad_norm": 0.1944192498922348,
715
+ "learning_rate": 0.00015512045872199276,
716
+ "loss": 0.5311,
717
+ "memory/device_reserved (GiB)": 139.06,
718
+ "memory/max_active (GiB)": 25.53,
719
+ "memory/max_allocated (GiB)": 25.53,
720
+ "ppl": 1.7008,
721
+ "step": 1325,
722
+ "tokens_per_second_per_gpu": 3655.12,
723
+ "total_tokens": 26164528
724
+ },
725
+ {
726
+ "epoch": 1.0127531882970742,
727
+ "grad_norm": 0.18358173966407776,
728
+ "learning_rate": 0.00015342735857451777,
729
+ "loss": 0.5145,
730
+ "memory/device_reserved (GiB)": 139.06,
731
+ "memory/max_active (GiB)": 25.53,
732
+ "memory/max_allocated (GiB)": 25.53,
733
+ "ppl": 1.6728,
734
+ "step": 1350,
735
+ "tokens_per_second_per_gpu": 4227.25,
736
+ "total_tokens": 26610460
737
+ },
738
+ {
739
+ "epoch": 1.0315078769692423,
740
+ "grad_norm": 0.1853465735912323,
741
+ "learning_rate": 0.00015171254687540038,
742
+ "loss": 0.5081,
743
+ "memory/device_reserved (GiB)": 139.06,
744
+ "memory/max_active (GiB)": 25.53,
745
+ "memory/max_allocated (GiB)": 25.53,
746
+ "ppl": 1.6621,
747
+ "step": 1375,
748
+ "tokens_per_second_per_gpu": 4318.88,
749
+ "total_tokens": 27064008
750
+ },
751
+ {
752
+ "epoch": 1.0502625656414104,
753
+ "grad_norm": 0.18925060331821442,
754
+ "learning_rate": 0.0001499767204815273,
755
+ "loss": 0.5185,
756
+ "memory/device_reserved (GiB)": 139.06,
757
+ "memory/max_active (GiB)": 25.53,
758
+ "memory/max_allocated (GiB)": 25.53,
759
+ "ppl": 1.6795,
760
+ "step": 1400,
761
+ "tokens_per_second_per_gpu": 4324.01,
762
+ "total_tokens": 27516590
763
+ },
764
+ {
765
+ "epoch": 1.0690172543135783,
766
+ "grad_norm": 0.20961470901966095,
767
+ "learning_rate": 0.00014822058478963532,
768
+ "loss": 0.5234,
769
+ "memory/device_reserved (GiB)": 139.06,
770
+ "memory/max_active (GiB)": 25.53,
771
+ "memory/max_allocated (GiB)": 25.53,
772
+ "ppl": 1.6878,
773
+ "step": 1425,
774
+ "tokens_per_second_per_gpu": 4319.64,
775
+ "total_tokens": 27970075
776
+ },
777
+ {
778
+ "epoch": 1.0877719429857464,
779
+ "grad_norm": 0.1982697695493698,
780
+ "learning_rate": 0.0001464448534496555,
781
+ "loss": 0.5169,
782
+ "memory/device_reserved (GiB)": 139.06,
783
+ "memory/max_active (GiB)": 25.53,
784
+ "memory/max_allocated (GiB)": 25.53,
785
+ "ppl": 1.6768,
786
+ "step": 1450,
787
+ "tokens_per_second_per_gpu": 4267.88,
788
+ "total_tokens": 28419716
789
+ },
790
+ {
791
+ "epoch": 1.1065266316579145,
792
+ "grad_norm": 0.1925143301486969,
793
+ "learning_rate": 0.00014465024807470376,
794
+ "loss": 0.5197,
795
+ "memory/device_reserved (GiB)": 139.06,
796
+ "memory/max_active (GiB)": 25.53,
797
+ "memory/max_allocated (GiB)": 25.53,
798
+ "ppl": 1.6815,
799
+ "step": 1475,
800
+ "tokens_per_second_per_gpu": 4264.53,
801
+ "total_tokens": 28866312
802
+ },
803
+ {
804
+ "epoch": 1.1252813203300824,
805
+ "grad_norm": 0.18788637220859528,
806
+ "learning_rate": 0.0001428374979478349,
807
+ "loss": 0.5204,
808
+ "memory/device_reserved (GiB)": 139.06,
809
+ "memory/max_active (GiB)": 25.53,
810
+ "memory/max_allocated (GiB)": 25.53,
811
+ "ppl": 1.6827,
812
+ "step": 1500,
813
+ "tokens_per_second_per_gpu": 3779.33,
814
+ "total_tokens": 29315968
815
+ },
816
+ {
817
+ "epoch": 1.1440360090022506,
818
+ "grad_norm": 0.18954145908355713,
819
+ "learning_rate": 0.00014100733972568038,
820
+ "loss": 0.5164,
821
+ "memory/device_reserved (GiB)": 139.06,
822
+ "memory/max_active (GiB)": 25.53,
823
+ "memory/max_allocated (GiB)": 25.53,
824
+ "ppl": 1.676,
825
+ "step": 1525,
826
+ "tokens_per_second_per_gpu": 4282.57,
827
+ "total_tokens": 29766723
828
+ },
829
+ {
830
+ "epoch": 1.1627906976744187,
831
+ "grad_norm": 0.19003146886825562,
832
+ "learning_rate": 0.00013916051713908924,
833
+ "loss": 0.5095,
834
+ "memory/device_reserved (GiB)": 139.06,
835
+ "memory/max_active (GiB)": 25.53,
836
+ "memory/max_allocated (GiB)": 25.53,
837
+ "ppl": 1.6645,
838
+ "step": 1550,
839
+ "tokens_per_second_per_gpu": 4290.76,
840
+ "total_tokens": 30218573
841
+ },
842
+ {
843
+ "epoch": 1.1815453863465866,
844
+ "grad_norm": 0.18279583752155304,
845
+ "learning_rate": 0.00013729778069089437,
846
+ "loss": 0.522,
847
+ "memory/device_reserved (GiB)": 139.06,
848
+ "memory/max_active (GiB)": 25.53,
849
+ "memory/max_allocated (GiB)": 25.53,
850
+ "ppl": 1.6854,
851
+ "step": 1575,
852
+ "tokens_per_second_per_gpu": 4300.13,
853
+ "total_tokens": 30669810
854
+ },
855
+ {
856
+ "epoch": 1.2003000750187547,
857
+ "grad_norm": 0.18783092498779297,
858
+ "learning_rate": 0.00013541988735092672,
859
+ "loss": 0.5003,
860
+ "memory/device_reserved (GiB)": 139.06,
861
+ "memory/max_active (GiB)": 25.53,
862
+ "memory/max_allocated (GiB)": 25.53,
863
+ "ppl": 1.6492,
864
+ "step": 1600,
865
+ "tokens_per_second_per_gpu": 4271.27,
866
+ "total_tokens": 31117586
867
+ },
868
+ {
869
+ "epoch": 1.2190547636909228,
870
+ "grad_norm": 0.199558824300766,
871
+ "learning_rate": 0.00013352760024840175,
872
+ "loss": 0.5115,
873
+ "memory/device_reserved (GiB)": 139.06,
874
+ "memory/max_active (GiB)": 25.53,
875
+ "memory/max_allocated (GiB)": 25.53,
876
+ "ppl": 1.6678,
877
+ "step": 1625,
878
+ "tokens_per_second_per_gpu": 4248.14,
879
+ "total_tokens": 31562224
880
+ },
881
+ {
882
+ "epoch": 1.2378094523630907,
883
+ "grad_norm": 0.19465653598308563,
884
+ "learning_rate": 0.00013162168836180246,
885
+ "loss": 0.4967,
886
+ "memory/device_reserved (GiB)": 139.06,
887
+ "memory/max_active (GiB)": 25.53,
888
+ "memory/max_allocated (GiB)": 25.53,
889
+ "ppl": 1.6433,
890
+ "step": 1650,
891
+ "tokens_per_second_per_gpu": 4286.24,
892
+ "total_tokens": 32011071
893
+ },
894
+ {
895
+ "epoch": 1.2565641410352588,
896
+ "grad_norm": 0.2054641842842102,
897
+ "learning_rate": 0.00012970292620638574,
898
+ "loss": 0.5172,
899
+ "memory/device_reserved (GiB)": 139.06,
900
+ "memory/max_active (GiB)": 25.53,
901
+ "memory/max_allocated (GiB)": 25.53,
902
+ "ppl": 1.6773,
903
+ "step": 1675,
904
+ "tokens_per_second_per_gpu": 3733.1,
905
+ "total_tokens": 32452490
906
+ },
907
+ {
908
+ "epoch": 1.275318829707427,
909
+ "grad_norm": 0.19450411200523376,
910
+ "learning_rate": 0.00012777209351943862,
911
+ "loss": 0.5149,
912
+ "memory/device_reserved (GiB)": 139.06,
913
+ "memory/max_active (GiB)": 25.53,
914
+ "memory/max_allocated (GiB)": 25.53,
915
+ "ppl": 1.6735,
916
+ "step": 1700,
917
+ "tokens_per_second_per_gpu": 4251.33,
918
+ "total_tokens": 32899103
919
+ },
920
+ {
921
+ "epoch": 1.2940735183795948,
922
+ "grad_norm": 0.19844166934490204,
923
+ "learning_rate": 0.0001258299749434123,
924
+ "loss": 0.5205,
925
+ "memory/device_reserved (GiB)": 139.06,
926
+ "memory/max_active (GiB)": 25.53,
927
+ "memory/max_allocated (GiB)": 25.53,
928
+ "ppl": 1.6829,
929
+ "step": 1725,
930
+ "tokens_per_second_per_gpu": 4240.57,
931
+ "total_tokens": 33344569
932
+ },
933
+ {
934
+ "epoch": 1.312828207051763,
935
+ "grad_norm": 0.19240470230579376,
936
+ "learning_rate": 0.00012387735970706312,
937
+ "loss": 0.5033,
938
+ "memory/device_reserved (GiB)": 139.06,
939
+ "memory/max_active (GiB)": 25.53,
940
+ "memory/max_allocated (GiB)": 25.53,
941
+ "ppl": 1.6542,
942
+ "step": 1750,
943
+ "tokens_per_second_per_gpu": 4267.65,
944
+ "total_tokens": 33790426
945
+ },
946
+ {
947
+ "epoch": 1.331582895723931,
948
+ "grad_norm": 0.18220192193984985,
949
+ "learning_rate": 0.00012191504130472937,
950
+ "loss": 0.5103,
951
+ "memory/device_reserved (GiB)": 139.06,
952
+ "memory/max_active (GiB)": 25.53,
953
+ "memory/max_allocated (GiB)": 25.53,
954
+ "ppl": 1.6658,
955
+ "step": 1775,
956
+ "tokens_per_second_per_gpu": 4237.08,
957
+ "total_tokens": 34233908
958
+ },
959
+ {
960
+ "epoch": 1.350337584396099,
961
+ "grad_norm": 0.20157551765441895,
962
+ "learning_rate": 0.00011994381717387514,
963
+ "loss": 0.5192,
964
+ "memory/device_reserved (GiB)": 139.06,
965
+ "memory/max_active (GiB)": 25.53,
966
+ "memory/max_allocated (GiB)": 25.53,
967
+ "ppl": 1.6807,
968
+ "step": 1800,
969
+ "tokens_per_second_per_gpu": 4244.09,
970
+ "total_tokens": 34678691
971
+ },
972
+ {
973
+ "epoch": 1.369092273068267,
974
+ "grad_norm": 0.17189238965511322,
975
+ "learning_rate": 0.00011796448837103129,
976
+ "loss": 0.5011,
977
+ "memory/device_reserved (GiB)": 139.06,
978
+ "memory/max_active (GiB)": 25.53,
979
+ "memory/max_allocated (GiB)": 25.53,
980
+ "ppl": 1.6505,
981
+ "step": 1825,
982
+ "tokens_per_second_per_gpu": 4277.26,
983
+ "total_tokens": 35125624
984
+ },
985
+ {
986
+ "epoch": 1.387846961740435,
987
+ "grad_norm": 0.19443106651306152,
988
+ "learning_rate": 0.00011597785924626616,
989
+ "loss": 0.4994,
990
+ "memory/device_reserved (GiB)": 139.06,
991
+ "memory/max_active (GiB)": 25.53,
992
+ "memory/max_allocated (GiB)": 25.53,
993
+ "ppl": 1.6477,
994
+ "step": 1850,
995
+ "tokens_per_second_per_gpu": 3766.52,
996
+ "total_tokens": 35568850
997
+ },
998
+ {
999
+ "epoch": 1.406601650412603,
1000
+ "grad_norm": 0.1810811311006546,
1001
+ "learning_rate": 0.00011398473711631764,
1002
+ "loss": 0.5083,
1003
+ "memory/device_reserved (GiB)": 139.06,
1004
+ "memory/max_active (GiB)": 25.53,
1005
+ "memory/max_allocated (GiB)": 25.53,
1006
+ "ppl": 1.6625,
1007
+ "step": 1875,
1008
+ "tokens_per_second_per_gpu": 4204.76,
1009
+ "total_tokens": 36009980
1010
+ },
1011
+ {
1012
+ "epoch": 1.4253563390847712,
1013
+ "grad_norm": 0.19805970788002014,
1014
+ "learning_rate": 0.00011198593193651958,
1015
+ "loss": 0.5141,
1016
+ "memory/device_reserved (GiB)": 139.06,
1017
+ "memory/max_active (GiB)": 25.53,
1018
+ "memory/max_allocated (GiB)": 25.53,
1019
+ "ppl": 1.6721,
1020
+ "step": 1900,
1021
+ "tokens_per_second_per_gpu": 4270.21,
1022
+ "total_tokens": 36457032
1023
+ },
1024
+ {
1025
+ "epoch": 1.4441110277569393,
1026
+ "grad_norm": 0.1936168372631073,
1027
+ "learning_rate": 0.00010998225597165628,
1028
+ "loss": 0.5045,
1029
+ "memory/device_reserved (GiB)": 139.06,
1030
+ "memory/max_active (GiB)": 25.53,
1031
+ "memory/max_allocated (GiB)": 25.53,
1032
+ "ppl": 1.6562,
1033
+ "step": 1925,
1034
+ "tokens_per_second_per_gpu": 4275.24,
1035
+ "total_tokens": 36905590
1036
+ },
1037
+ {
1038
+ "epoch": 1.4628657164291072,
1039
+ "grad_norm": 0.19065748155117035,
1040
+ "learning_rate": 0.00010797452346587798,
1041
+ "loss": 0.5025,
1042
+ "memory/device_reserved (GiB)": 139.06,
1043
+ "memory/max_active (GiB)": 25.53,
1044
+ "memory/max_allocated (GiB)": 25.53,
1045
+ "ppl": 1.6528,
1046
+ "step": 1950,
1047
+ "tokens_per_second_per_gpu": 4285.81,
1048
+ "total_tokens": 37354436
1049
+ },
1050
+ {
1051
+ "epoch": 1.4816204051012754,
1052
+ "grad_norm": 0.18647657334804535,
1053
+ "learning_rate": 0.0001059635503118125,
1054
+ "loss": 0.5102,
1055
+ "memory/device_reserved (GiB)": 139.06,
1056
+ "memory/max_active (GiB)": 25.53,
1057
+ "memory/max_allocated (GiB)": 25.53,
1058
+ "ppl": 1.6656,
1059
+ "step": 1975,
1060
+ "tokens_per_second_per_gpu": 4259.76,
1061
+ "total_tokens": 37801500
1062
+ },
1063
+ {
1064
+ "epoch": 1.5003750937734432,
1065
+ "grad_norm": 0.21211788058280945,
1066
+ "learning_rate": 0.00010395015371900663,
1067
+ "loss": 0.5052,
1068
+ "memory/device_reserved (GiB)": 139.06,
1069
+ "memory/max_active (GiB)": 25.53,
1070
+ "memory/max_allocated (GiB)": 25.53,
1071
+ "ppl": 1.6573,
1072
+ "step": 2000,
1073
+ "tokens_per_second_per_gpu": 4250.7,
1074
+ "total_tokens": 38244936
1075
+ },
1076
+ {
1077
+ "epoch": 1.5003750937734432,
1078
+ "eval_loss": 0.5063687562942505,
1079
+ "eval_ppl": 1.6593,
1080
+ "eval_runtime": 141.112,
1081
+ "eval_samples_per_second": 5.173,
1082
+ "eval_steps_per_second": 1.035,
1083
+ "memory/device_reserved (GiB)": 139.06,
1084
+ "memory/max_active (GiB)": 19.1,
1085
+ "memory/max_allocated (GiB)": 19.1,
1086
+ "step": 2000
1087
+ },
1088
+ {
1089
+ "epoch": 1.5191297824456114,
1090
+ "grad_norm": 0.20089760422706604,
1091
+ "learning_rate": 0.00010193515188183245,
1092
+ "loss": 0.4892,
1093
+ "memory/device_reserved (GiB)": 139.06,
1094
+ "memory/max_active (GiB)": 25.53,
1095
+ "memory/max_allocated (GiB)": 25.53,
1096
+ "ppl": 1.631,
1097
+ "step": 2025,
1098
+ "tokens_per_second_per_gpu": 4246.58,
1099
+ "total_tokens": 39959888
1100
+ },
1101
+ {
1102
+ "epoch": 1.5378844711177795,
1103
+ "grad_norm": 0.19840118288993835,
1104
+ "learning_rate": 9.991936364699348e-05,
1105
+ "loss": 0.503,
1106
+ "memory/device_reserved (GiB)": 139.06,
1107
+ "memory/max_active (GiB)": 25.53,
1108
+ "memory/max_allocated (GiB)": 25.53,
1109
+ "ppl": 1.6537,
1110
+ "step": 2050,
1111
+ "tokens_per_second_per_gpu": 4320.38,
1112
+ "total_tokens": 40411902
1113
+ },
1114
+ {
1115
+ "epoch": 1.5566391597899476,
1116
+ "grad_norm": 0.20045842230319977,
1117
+ "learning_rate": 9.790360818076577e-05,
1118
+ "loss": 0.5127,
1119
+ "memory/device_reserved (GiB)": 139.06,
1120
+ "memory/max_active (GiB)": 25.53,
1121
+ "memory/max_allocated (GiB)": 25.53,
1122
+ "ppl": 1.6698,
1123
+ "step": 2075,
1124
+ "tokens_per_second_per_gpu": 4245.02,
1125
+ "total_tokens": 40855384
1126
+ },
1127
+ {
1128
+ "epoch": 1.5753938484621155,
1129
+ "grad_norm": 0.19669026136398315,
1130
+ "learning_rate": 9.588870463610893e-05,
1131
+ "loss": 0.4994,
1132
+ "memory/device_reserved (GiB)": 139.06,
1133
+ "memory/max_active (GiB)": 25.53,
1134
+ "memory/max_allocated (GiB)": 25.53,
1135
+ "ppl": 1.6477,
1136
+ "step": 2100,
1137
+ "tokens_per_second_per_gpu": 4174.18,
1138
+ "total_tokens": 41293525
1139
+ },
1140
+ {
1141
+ "epoch": 1.5941485371342836,
1142
+ "grad_norm": 0.19754259288311005,
1143
+ "learning_rate": 9.387547181978291e-05,
1144
+ "loss": 0.5009,
1145
+ "memory/device_reserved (GiB)": 139.06,
1146
+ "memory/max_active (GiB)": 25.53,
1147
+ "memory/max_allocated (GiB)": 25.53,
1148
+ "ppl": 1.6502,
1149
+ "step": 2125,
1150
+ "tokens_per_second_per_gpu": 4200.06,
1151
+ "total_tokens": 41737747
1152
+ },
1153
+ {
1154
+ "epoch": 1.6129032258064515,
1155
+ "grad_norm": 0.19482502341270447,
1156
+ "learning_rate": 9.186472785960507e-05,
1157
+ "loss": 0.5002,
1158
+ "memory/device_reserved (GiB)": 139.06,
1159
+ "memory/max_active (GiB)": 25.53,
1160
+ "memory/max_allocated (GiB)": 25.53,
1161
+ "ppl": 1.6491,
1162
+ "step": 2150,
1163
+ "tokens_per_second_per_gpu": 3696.76,
1164
+ "total_tokens": 42176082
1165
+ },
1166
+ {
1167
+ "epoch": 1.6316579144786196,
1168
+ "grad_norm": 0.21606561541557312,
1169
+ "learning_rate": 8.985728987198352e-05,
1170
+ "loss": 0.4959,
1171
+ "memory/device_reserved (GiB)": 139.06,
1172
+ "memory/max_active (GiB)": 25.53,
1173
+ "memory/max_allocated (GiB)": 25.53,
1174
+ "ppl": 1.642,
1175
+ "step": 2175,
1176
+ "tokens_per_second_per_gpu": 4192.5,
1177
+ "total_tokens": 42616372
1178
+ },
1179
+ {
1180
+ "epoch": 1.6504126031507877,
1181
+ "grad_norm": 0.1979638934135437,
1182
+ "learning_rate": 8.785397362986114e-05,
1183
+ "loss": 0.5031,
1184
+ "memory/device_reserved (GiB)": 139.06,
1185
+ "memory/max_active (GiB)": 25.53,
1186
+ "memory/max_allocated (GiB)": 25.53,
1187
+ "ppl": 1.6538,
1188
+ "step": 2200,
1189
+ "tokens_per_second_per_gpu": 4211.67,
1190
+ "total_tokens": 43058315
1191
+ },
1192
+ {
1193
+ "epoch": 1.6691672918229559,
1194
+ "grad_norm": 0.20717743039131165,
1195
+ "learning_rate": 8.58555932312059e-05,
1196
+ "loss": 0.4986,
1197
+ "memory/device_reserved (GiB)": 139.06,
1198
+ "memory/max_active (GiB)": 25.53,
1199
+ "memory/max_allocated (GiB)": 25.53,
1200
+ "ppl": 1.6464,
1201
+ "step": 2225,
1202
+ "tokens_per_second_per_gpu": 4242.04,
1203
+ "total_tokens": 43501960
1204
+ },
1205
+ {
1206
+ "epoch": 1.6879219804951238,
1207
+ "grad_norm": 0.18736609816551208,
1208
+ "learning_rate": 8.38629607681815e-05,
1209
+ "loss": 0.4898,
1210
+ "memory/device_reserved (GiB)": 139.06,
1211
+ "memory/max_active (GiB)": 25.53,
1212
+ "memory/max_allocated (GiB)": 25.53,
1213
+ "ppl": 1.632,
1214
+ "step": 2250,
1215
+ "tokens_per_second_per_gpu": 4235.21,
1216
+ "total_tokens": 43947235
1217
+ },
1218
+ {
1219
+ "epoch": 1.7066766691672917,
1220
+ "grad_norm": 0.2056591659784317,
1221
+ "learning_rate": 8.187688599713333e-05,
1222
+ "loss": 0.4925,
1223
+ "memory/device_reserved (GiB)": 139.06,
1224
+ "memory/max_active (GiB)": 25.53,
1225
+ "memory/max_allocated (GiB)": 25.53,
1226
+ "ppl": 1.6364,
1227
+ "step": 2275,
1228
+ "tokens_per_second_per_gpu": 4256.41,
1229
+ "total_tokens": 44393451
1230
+ },
1231
+ {
1232
+ "epoch": 1.7254313578394598,
1233
+ "grad_norm": 0.19774597883224487,
1234
+ "learning_rate": 7.989817600952376e-05,
1235
+ "loss": 0.4952,
1236
+ "memory/device_reserved (GiB)": 139.06,
1237
+ "memory/max_active (GiB)": 25.53,
1238
+ "memory/max_allocated (GiB)": 25.53,
1239
+ "ppl": 1.6408,
1240
+ "step": 2300,
1241
+ "tokens_per_second_per_gpu": 4224.5,
1242
+ "total_tokens": 44836590
1243
+ },
1244
+ {
1245
+ "epoch": 1.744186046511628,
1246
+ "grad_norm": 0.19662383198738098,
1247
+ "learning_rate": 7.792763490394984e-05,
1248
+ "loss": 0.4977,
1249
+ "memory/device_reserved (GiB)": 139.06,
1250
+ "memory/max_active (GiB)": 25.53,
1251
+ "memory/max_allocated (GiB)": 25.53,
1252
+ "ppl": 1.6449,
1253
+ "step": 2325,
1254
+ "tokens_per_second_per_gpu": 3741.52,
1255
+ "total_tokens": 45279799
1256
+ },
1257
+ {
1258
+ "epoch": 1.762940735183796,
1259
+ "grad_norm": 0.19400179386138916,
1260
+ "learning_rate": 7.596606345937812e-05,
1261
+ "loss": 0.4965,
1262
+ "memory/device_reserved (GiB)": 139.06,
1263
+ "memory/max_active (GiB)": 25.53,
1264
+ "memory/max_allocated (GiB)": 25.53,
1265
+ "ppl": 1.643,
1266
+ "step": 2350,
1267
+ "tokens_per_second_per_gpu": 4248.51,
1268
+ "total_tokens": 45725602
1269
+ },
1270
+ {
1271
+ "epoch": 1.7816954238559641,
1272
+ "grad_norm": 0.20261766016483307,
1273
+ "learning_rate": 7.401425880972742e-05,
1274
+ "loss": 0.5014,
1275
+ "memory/device_reserved (GiB)": 139.06,
1276
+ "memory/max_active (GiB)": 25.53,
1277
+ "memory/max_allocated (GiB)": 25.53,
1278
+ "ppl": 1.651,
1279
+ "step": 2375,
1280
+ "tokens_per_second_per_gpu": 4216.2,
1281
+ "total_tokens": 46167730
1282
+ },
1283
+ {
1284
+ "epoch": 1.800450112528132,
1285
+ "grad_norm": 0.20447255671024323,
1286
+ "learning_rate": 7.207301411993387e-05,
1287
+ "loss": 0.4901,
1288
+ "memory/device_reserved (GiB)": 139.06,
1289
+ "memory/max_active (GiB)": 25.53,
1290
+ "memory/max_allocated (GiB)": 25.53,
1291
+ "ppl": 1.6325,
1292
+ "step": 2400,
1293
+ "tokens_per_second_per_gpu": 3727.37,
1294
+ "total_tokens": 46611126
1295
+ },
1296
+ {
1297
+ "epoch": 1.8192048012003,
1298
+ "grad_norm": 0.19921696186065674,
1299
+ "learning_rate": 7.014311826362804e-05,
1300
+ "loss": 0.4925,
1301
+ "memory/device_reserved (GiB)": 139.06,
1302
+ "memory/max_active (GiB)": 25.53,
1303
+ "memory/max_allocated (GiB)": 25.53,
1304
+ "ppl": 1.6364,
1305
+ "step": 2425,
1306
+ "tokens_per_second_per_gpu": 4202.19,
1307
+ "total_tokens": 47050763
1308
+ },
1309
+ {
1310
+ "epoch": 1.837959489872468,
1311
+ "grad_norm": 0.20095540583133698,
1312
+ "learning_rate": 6.822535550255652e-05,
1313
+ "loss": 0.494,
1314
+ "memory/device_reserved (GiB)": 139.06,
1315
+ "memory/max_active (GiB)": 25.53,
1316
+ "memory/max_allocated (GiB)": 25.53,
1317
+ "ppl": 1.6389,
1318
+ "step": 2450,
1319
+ "tokens_per_second_per_gpu": 4230.16,
1320
+ "total_tokens": 47496926
1321
+ },
1322
+ {
1323
+ "epoch": 1.8567141785446362,
1324
+ "grad_norm": 0.20210741460323334,
1325
+ "learning_rate": 6.632050516787719e-05,
1326
+ "loss": 0.5036,
1327
+ "memory/device_reserved (GiB)": 139.06,
1328
+ "memory/max_active (GiB)": 25.53,
1329
+ "memory/max_allocated (GiB)": 25.53,
1330
+ "ppl": 1.6547,
1331
+ "step": 2475,
1332
+ "tokens_per_second_per_gpu": 4256.1,
1333
+ "total_tokens": 47941250
1334
+ },
1335
+ {
1336
+ "epoch": 1.8754688672168043,
1337
+ "grad_norm": 0.21025419235229492,
1338
+ "learning_rate": 6.442934134345871e-05,
1339
+ "loss": 0.5019,
1340
+ "memory/device_reserved (GiB)": 139.06,
1341
+ "memory/max_active (GiB)": 25.53,
1342
+ "memory/max_allocated (GiB)": 25.53,
1343
+ "ppl": 1.6519,
1344
+ "step": 2500,
1345
+ "tokens_per_second_per_gpu": 3728.09,
1346
+ "total_tokens": 48383306
1347
+ },
1348
+ {
1349
+ "epoch": 1.8942235558889724,
1350
+ "grad_norm": 0.20130059123039246,
1351
+ "learning_rate": 6.255263255131172e-05,
1352
+ "loss": 0.5022,
1353
+ "memory/device_reserved (GiB)": 139.06,
1354
+ "memory/max_active (GiB)": 25.53,
1355
+ "memory/max_allocated (GiB)": 25.53,
1356
+ "ppl": 1.6524,
1357
+ "step": 2525,
1358
+ "tokens_per_second_per_gpu": 4178.95,
1359
+ "total_tokens": 48821862
1360
+ },
1361
+ {
1362
+ "epoch": 1.9129782445611403,
1363
+ "grad_norm": 0.19601669907569885,
1364
+ "learning_rate": 6.0691141439280785e-05,
1365
+ "loss": 0.4876,
1366
+ "memory/device_reserved (GiB)": 139.06,
1367
+ "memory/max_active (GiB)": 25.53,
1368
+ "memory/max_allocated (GiB)": 25.53,
1369
+ "ppl": 1.6284,
1370
+ "step": 2550,
1371
+ "tokens_per_second_per_gpu": 3998.52,
1372
+ "total_tokens": 49262344
1373
+ },
1374
+ {
1375
+ "epoch": 1.9317329332333082,
1376
+ "grad_norm": 0.20538586378097534,
1377
+ "learning_rate": 5.884562447112331e-05,
1378
+ "loss": 0.4796,
1379
+ "memory/device_reserved (GiB)": 139.06,
1380
+ "memory/max_active (GiB)": 25.53,
1381
+ "memory/max_allocated (GiB)": 25.53,
1382
+ "ppl": 1.6154,
1383
+ "step": 2575,
1384
+ "tokens_per_second_per_gpu": 4192.8,
1385
+ "total_tokens": 49702209
1386
+ },
1387
+ {
1388
+ "epoch": 1.9504876219054763,
1389
+ "grad_norm": 0.19957959651947021,
1390
+ "learning_rate": 5.701683161910115e-05,
1391
+ "loss": 0.5017,
1392
+ "memory/device_reserved (GiB)": 139.06,
1393
+ "memory/max_active (GiB)": 25.53,
1394
+ "memory/max_allocated (GiB)": 25.53,
1395
+ "ppl": 1.6515,
1396
+ "step": 2600,
1397
+ "tokens_per_second_per_gpu": 4244.94,
1398
+ "total_tokens": 50147673
1399
+ },
1400
+ {
1401
+ "epoch": 1.9692423105776444,
1402
+ "grad_norm": 0.20284536480903625,
1403
+ "learning_rate": 5.520550605921091e-05,
1404
+ "loss": 0.5024,
1405
+ "memory/device_reserved (GiB)": 139.06,
1406
+ "memory/max_active (GiB)": 25.53,
1407
+ "memory/max_allocated (GiB)": 25.53,
1408
+ "ppl": 1.6527,
1409
+ "step": 2625,
1410
+ "tokens_per_second_per_gpu": 4205.45,
1411
+ "total_tokens": 50589478
1412
+ },
1413
+ {
1414
+ "epoch": 1.9879969992498125,
1415
+ "grad_norm": 0.2044789344072342,
1416
+ "learning_rate": 5.34123838691753e-05,
1417
+ "loss": 0.4967,
1418
+ "memory/device_reserved (GiB)": 139.06,
1419
+ "memory/max_active (GiB)": 25.53,
1420
+ "memory/max_allocated (GiB)": 25.53,
1421
+ "ppl": 1.6433,
1422
+ "step": 2650,
1423
+ "tokens_per_second_per_gpu": 4204.9,
1424
+ "total_tokens": 51027800
1425
+ },
1426
+ {
1427
+ "epoch": 2.0067516879219807,
1428
+ "grad_norm": 0.2125943899154663,
1429
+ "learning_rate": 5.163819372931979e-05,
1430
+ "loss": 0.4862,
1431
+ "memory/device_reserved (GiB)": 139.06,
1432
+ "memory/max_active (GiB)": 25.53,
1433
+ "memory/max_allocated (GiB)": 25.53,
1434
+ "ppl": 1.6261,
1435
+ "step": 2675,
1436
+ "tokens_per_second_per_gpu": 3745.54,
1437
+ "total_tokens": 51469941
1438
+ },
1439
+ {
1440
+ "epoch": 2.0255063765941483,
1441
+ "grad_norm": 0.2312517911195755,
1442
+ "learning_rate": 4.9883656626454724e-05,
1443
+ "loss": 0.4782,
1444
+ "memory/device_reserved (GiB)": 139.06,
1445
+ "memory/max_active (GiB)": 25.53,
1446
+ "memory/max_allocated (GiB)": 25.53,
1447
+ "ppl": 1.6132,
1448
+ "step": 2700,
1449
+ "tokens_per_second_per_gpu": 4275.5,
1450
+ "total_tokens": 51921057
1451
+ },
1452
+ {
1453
+ "epoch": 2.0442610652663165,
1454
+ "grad_norm": 0.19745635986328125,
1455
+ "learning_rate": 4.81494855608843e-05,
1456
+ "loss": 0.4717,
1457
+ "memory/device_reserved (GiB)": 139.06,
1458
+ "memory/max_active (GiB)": 25.53,
1459
+ "memory/max_allocated (GiB)": 25.53,
1460
+ "ppl": 1.6027,
1461
+ "step": 2725,
1462
+ "tokens_per_second_per_gpu": 4290.88,
1463
+ "total_tokens": 52372623
1464
+ },
1465
+ {
1466
+ "epoch": 2.0630157539384846,
1467
+ "grad_norm": 0.22817276418209076,
1468
+ "learning_rate": 4.643638525666095e-05,
1469
+ "loss": 0.4817,
1470
+ "memory/device_reserved (GiB)": 139.06,
1471
+ "memory/max_active (GiB)": 25.53,
1472
+ "memory/max_allocated (GiB)": 25.53,
1473
+ "ppl": 1.6188,
1474
+ "step": 2750,
1475
+ "tokens_per_second_per_gpu": 4292.31,
1476
+ "total_tokens": 52823263
1477
+ },
1478
+ {
1479
+ "epoch": 2.0817704426106527,
1480
+ "grad_norm": 0.20878754556179047,
1481
+ "learning_rate": 4.4745051875203134e-05,
1482
+ "loss": 0.4774,
1483
+ "memory/device_reserved (GiB)": 139.06,
1484
+ "memory/max_active (GiB)": 25.53,
1485
+ "memory/max_allocated (GiB)": 25.53,
1486
+ "ppl": 1.6119,
1487
+ "step": 2775,
1488
+ "tokens_per_second_per_gpu": 4287.12,
1489
+ "total_tokens": 53272669
1490
+ },
1491
+ {
1492
+ "epoch": 2.100525131282821,
1493
+ "grad_norm": 0.18676196038722992,
1494
+ "learning_rate": 4.307617273239226e-05,
1495
+ "loss": 0.4824,
1496
+ "memory/device_reserved (GiB)": 139.06,
1497
+ "memory/max_active (GiB)": 25.53,
1498
+ "memory/max_allocated (GiB)": 25.53,
1499
+ "ppl": 1.62,
1500
+ "step": 2800,
1501
+ "tokens_per_second_per_gpu": 4304.14,
1502
+ "total_tokens": 53724750
1503
+ },
1504
+ {
1505
+ "epoch": 2.119279819954989,
1506
+ "grad_norm": 0.20670537650585175,
1507
+ "learning_rate": 4.1430426019264924e-05,
1508
+ "loss": 0.4701,
1509
+ "memory/device_reserved (GiB)": 139.06,
1510
+ "memory/max_active (GiB)": 25.53,
1511
+ "memory/max_allocated (GiB)": 25.53,
1512
+ "ppl": 1.6002,
1513
+ "step": 2825,
1514
+ "tokens_per_second_per_gpu": 4283.76,
1515
+ "total_tokens": 54172957
1516
+ },
1517
+ {
1518
+ "epoch": 2.1380345086271566,
1519
+ "grad_norm": 0.21445906162261963,
1520
+ "learning_rate": 3.980848052641286e-05,
1521
+ "loss": 0.4772,
1522
+ "memory/device_reserved (GiB)": 139.06,
1523
+ "memory/max_active (GiB)": 25.53,
1524
+ "memory/max_allocated (GiB)": 25.53,
1525
+ "ppl": 1.6116,
1526
+ "step": 2850,
1527
+ "tokens_per_second_per_gpu": 3768.93,
1528
+ "total_tokens": 54625827
1529
+ },
1530
+ {
1531
+ "epoch": 2.1567891972993247,
1532
+ "grad_norm": 0.21021129190921783,
1533
+ "learning_rate": 3.8210995372202896e-05,
1534
+ "loss": 0.471,
1535
+ "memory/device_reserved (GiB)": 139.06,
1536
+ "memory/max_active (GiB)": 25.53,
1537
+ "memory/max_allocated (GiB)": 25.53,
1538
+ "ppl": 1.6016,
1539
+ "step": 2875,
1540
+ "tokens_per_second_per_gpu": 4286.55,
1541
+ "total_tokens": 55076031
1542
+ },
1543
+ {
1544
+ "epoch": 2.175543885971493,
1545
+ "grad_norm": 0.23069453239440918,
1546
+ "learning_rate": 3.663861973492776e-05,
1547
+ "loss": 0.4722,
1548
+ "memory/device_reserved (GiB)": 139.06,
1549
+ "memory/max_active (GiB)": 25.53,
1550
+ "memory/max_allocated (GiB)": 25.53,
1551
+ "ppl": 1.6035,
1552
+ "step": 2900,
1553
+ "tokens_per_second_per_gpu": 4291.53,
1554
+ "total_tokens": 55527864
1555
+ },
1556
+ {
1557
+ "epoch": 2.194298574643661,
1558
+ "grad_norm": 0.22328485548496246,
1559
+ "learning_rate": 3.509199258899603e-05,
1560
+ "loss": 0.474,
1561
+ "memory/device_reserved (GiB)": 139.06,
1562
+ "memory/max_active (GiB)": 25.53,
1563
+ "memory/max_allocated (GiB)": 25.53,
1564
+ "ppl": 1.6064,
1565
+ "step": 2925,
1566
+ "tokens_per_second_per_gpu": 4262.17,
1567
+ "total_tokens": 55976245
1568
+ },
1569
+ {
1570
+ "epoch": 2.213053263315829,
1571
+ "grad_norm": 0.20422938466072083,
1572
+ "learning_rate": 3.3571742445268995e-05,
1573
+ "loss": 0.4721,
1574
+ "memory/device_reserved (GiB)": 139.06,
1575
+ "memory/max_active (GiB)": 25.53,
1576
+ "memory/max_allocated (GiB)": 25.53,
1577
+ "ppl": 1.6034,
1578
+ "step": 2950,
1579
+ "tokens_per_second_per_gpu": 4339.03,
1580
+ "total_tokens": 56430293
1581
+ },
1582
+ {
1583
+ "epoch": 2.231807951987997,
1584
+ "grad_norm": 0.21462033689022064,
1585
+ "learning_rate": 3.2078487095649236e-05,
1586
+ "loss": 0.4798,
1587
+ "memory/device_reserved (GiB)": 139.06,
1588
+ "memory/max_active (GiB)": 25.53,
1589
+ "memory/max_allocated (GiB)": 25.53,
1590
+ "ppl": 1.6158,
1591
+ "step": 2975,
1592
+ "tokens_per_second_per_gpu": 4274.93,
1593
+ "total_tokens": 56879796
1594
+ },
1595
+ {
1596
+ "epoch": 2.250562640660165,
1597
+ "grad_norm": 0.21800526976585388,
1598
+ "learning_rate": 3.061283336202545e-05,
1599
+ "loss": 0.4733,
1600
+ "memory/device_reserved (GiB)": 139.06,
1601
+ "memory/max_active (GiB)": 25.53,
1602
+ "memory/max_allocated (GiB)": 25.53,
1603
+ "ppl": 1.6053,
1604
+ "step": 3000,
1605
+ "tokens_per_second_per_gpu": 4290.7,
1606
+ "total_tokens": 57329902
1607
+ },
1608
+ {
1609
+ "epoch": 2.250562640660165,
1610
+ "eval_loss": 0.49272674322128296,
1611
+ "eval_ppl": 1.6368,
1612
+ "eval_runtime": 139.4189,
1613
+ "eval_samples_per_second": 5.236,
1614
+ "eval_steps_per_second": 1.047,
1615
+ "memory/device_reserved (GiB)": 139.06,
1616
+ "memory/max_active (GiB)": 19.1,
1617
+ "memory/max_allocated (GiB)": 19.1,
1618
+ "step": 3000
1619
+ },
1620
+ {
1621
+ "epoch": 2.269317329332333,
1622
+ "grad_norm": 0.23463094234466553,
1623
+ "learning_rate": 2.9175376849675073e-05,
1624
+ "loss": 0.4705,
1625
+ "memory/device_reserved (GiB)": 139.06,
1626
+ "memory/max_active (GiB)": 25.53,
1627
+ "memory/max_allocated (GiB)": 25.53,
1628
+ "ppl": 1.6008,
1629
+ "step": 3025,
1630
+ "tokens_per_second_per_gpu": 4276.0,
1631
+ "total_tokens": 59047769
1632
+ },
1633
+ {
1634
+ "epoch": 2.288072018004501,
1635
+ "grad_norm": 0.2144247442483902,
1636
+ "learning_rate": 2.7766701705225194e-05,
1637
+ "loss": 0.4761,
1638
+ "memory/device_reserved (GiB)": 139.06,
1639
+ "memory/max_active (GiB)": 25.53,
1640
+ "memory/max_allocated (GiB)": 25.53,
1641
+ "ppl": 1.6098,
1642
+ "step": 3050,
1643
+ "tokens_per_second_per_gpu": 4257.17,
1644
+ "total_tokens": 59495040
1645
+ },
1646
+ {
1647
+ "epoch": 2.3068267066766692,
1648
+ "grad_norm": 0.21562626957893372,
1649
+ "learning_rate": 2.6387380379269623e-05,
1650
+ "loss": 0.4576,
1651
+ "memory/device_reserved (GiB)": 139.06,
1652
+ "memory/max_active (GiB)": 25.53,
1653
+ "memory/max_allocated (GiB)": 25.53,
1654
+ "ppl": 1.5803,
1655
+ "step": 3075,
1656
+ "tokens_per_second_per_gpu": 4276.33,
1657
+ "total_tokens": 59941839
1658
+ },
1659
+ {
1660
+ "epoch": 2.3255813953488373,
1661
+ "grad_norm": 0.2173856496810913,
1662
+ "learning_rate": 2.5037973393739433e-05,
1663
+ "loss": 0.4578,
1664
+ "memory/device_reserved (GiB)": 139.06,
1665
+ "memory/max_active (GiB)": 25.53,
1666
+ "memory/max_allocated (GiB)": 25.53,
1667
+ "ppl": 1.5806,
1668
+ "step": 3100,
1669
+ "tokens_per_second_per_gpu": 4284.31,
1670
+ "total_tokens": 60392267
1671
+ },
1672
+ {
1673
+ "epoch": 2.3443360840210055,
1674
+ "grad_norm": 0.21864096820354462,
1675
+ "learning_rate": 2.3719029114120716e-05,
1676
+ "loss": 0.4652,
1677
+ "memory/device_reserved (GiB)": 139.06,
1678
+ "memory/max_active (GiB)": 25.53,
1679
+ "memory/max_allocated (GiB)": 25.53,
1680
+ "ppl": 1.5923,
1681
+ "step": 3125,
1682
+ "tokens_per_second_per_gpu": 4250.05,
1683
+ "total_tokens": 60836393
1684
+ },
1685
+ {
1686
+ "epoch": 2.363090772693173,
1687
+ "grad_norm": 0.22768662869930267,
1688
+ "learning_rate": 2.2431083526612373e-05,
1689
+ "loss": 0.4721,
1690
+ "memory/device_reserved (GiB)": 139.06,
1691
+ "memory/max_active (GiB)": 25.53,
1692
+ "memory/max_allocated (GiB)": 25.53,
1693
+ "ppl": 1.6034,
1694
+ "step": 3150,
1695
+ "tokens_per_second_per_gpu": 3777.63,
1696
+ "total_tokens": 61282878
1697
+ },
1698
+ {
1699
+ "epoch": 2.3818454613653413,
1700
+ "grad_norm": 0.20161285996437073,
1701
+ "learning_rate": 2.1174660020314696e-05,
1702
+ "loss": 0.486,
1703
+ "memory/device_reserved (GiB)": 139.06,
1704
+ "memory/max_active (GiB)": 25.53,
1705
+ "memory/max_allocated (GiB)": 25.53,
1706
+ "ppl": 1.6258,
1707
+ "step": 3175,
1708
+ "tokens_per_second_per_gpu": 4279.7,
1709
+ "total_tokens": 61731262
1710
+ },
1711
+ {
1712
+ "epoch": 2.4006001500375094,
1713
+ "grad_norm": 0.2132490575313568,
1714
+ "learning_rate": 1.9950269174537007e-05,
1715
+ "loss": 0.4822,
1716
+ "memory/device_reserved (GiB)": 139.06,
1717
+ "memory/max_active (GiB)": 25.53,
1718
+ "memory/max_allocated (GiB)": 25.53,
1719
+ "ppl": 1.6196,
1720
+ "step": 3200,
1721
+ "tokens_per_second_per_gpu": 4245.52,
1722
+ "total_tokens": 62179118
1723
+ },
1724
+ {
1725
+ "epoch": 2.4193548387096775,
1726
+ "grad_norm": 0.24689531326293945,
1727
+ "learning_rate": 1.8758408551311047e-05,
1728
+ "loss": 0.49,
1729
+ "memory/device_reserved (GiB)": 139.06,
1730
+ "memory/max_active (GiB)": 25.53,
1731
+ "memory/max_allocated (GiB)": 25.53,
1732
+ "ppl": 1.6323,
1733
+ "step": 3225,
1734
+ "tokens_per_second_per_gpu": 4237.8,
1735
+ "total_tokens": 62624159
1736
+ },
1737
+ {
1738
+ "epoch": 2.4381095273818456,
1739
+ "grad_norm": 0.2103738784790039,
1740
+ "learning_rate": 1.7599562493193867e-05,
1741
+ "loss": 0.4654,
1742
+ "memory/device_reserved (GiB)": 139.06,
1743
+ "memory/max_active (GiB)": 25.53,
1744
+ "memory/max_allocated (GiB)": 25.53,
1745
+ "ppl": 1.5927,
1746
+ "step": 3250,
1747
+ "tokens_per_second_per_gpu": 4234.16,
1748
+ "total_tokens": 63069936
1749
+ },
1750
+ {
1751
+ "epoch": 2.4568642160540133,
1752
+ "grad_norm": 0.2107544094324112,
1753
+ "learning_rate": 1.6474201926443267e-05,
1754
+ "loss": 0.4575,
1755
+ "memory/device_reserved (GiB)": 139.06,
1756
+ "memory/max_active (GiB)": 25.53,
1757
+ "memory/max_allocated (GiB)": 25.53,
1758
+ "ppl": 1.5801,
1759
+ "step": 3275,
1760
+ "tokens_per_second_per_gpu": 4198.5,
1761
+ "total_tokens": 63512282
1762
+ },
1763
+ {
1764
+ "epoch": 2.4756189047261814,
1765
+ "grad_norm": 0.211527019739151,
1766
+ "learning_rate": 1.5382784169644925e-05,
1767
+ "loss": 0.4654,
1768
+ "memory/device_reserved (GiB)": 139.06,
1769
+ "memory/max_active (GiB)": 25.53,
1770
+ "memory/max_allocated (GiB)": 25.53,
1771
+ "ppl": 1.5927,
1772
+ "step": 3300,
1773
+ "tokens_per_second_per_gpu": 4266.77,
1774
+ "total_tokens": 63959153
1775
+ },
1776
+ {
1777
+ "epoch": 2.4943735933983495,
1778
+ "grad_norm": 0.22054381668567657,
1779
+ "learning_rate": 1.4325752747869626e-05,
1780
+ "loss": 0.4601,
1781
+ "memory/device_reserved (GiB)": 139.06,
1782
+ "memory/max_active (GiB)": 25.53,
1783
+ "memory/max_allocated (GiB)": 25.53,
1784
+ "ppl": 1.5842,
1785
+ "step": 3325,
1786
+ "tokens_per_second_per_gpu": 3810.76,
1787
+ "total_tokens": 64408084
1788
+ },
1789
+ {
1790
+ "epoch": 2.5131282820705176,
1791
+ "grad_norm": 0.21859121322631836,
1792
+ "learning_rate": 1.3303537212435469e-05,
1793
+ "loss": 0.4594,
1794
+ "memory/device_reserved (GiB)": 139.06,
1795
+ "memory/max_active (GiB)": 25.53,
1796
+ "memory/max_allocated (GiB)": 25.53,
1797
+ "ppl": 1.5831,
1798
+ "step": 3350,
1799
+ "tokens_per_second_per_gpu": 4141.07,
1800
+ "total_tokens": 64850022
1801
+ },
1802
+ {
1803
+ "epoch": 2.5318829707426858,
1804
+ "grad_norm": 0.22012574970722198,
1805
+ "learning_rate": 1.231655296634906e-05,
1806
+ "loss": 0.4635,
1807
+ "memory/device_reserved (GiB)": 139.06,
1808
+ "memory/max_active (GiB)": 25.53,
1809
+ "memory/max_allocated (GiB)": 25.53,
1810
+ "ppl": 1.5896,
1811
+ "step": 3375,
1812
+ "tokens_per_second_per_gpu": 4210.83,
1813
+ "total_tokens": 65292271
1814
+ },
1815
+ {
1816
+ "epoch": 2.550637659414854,
1817
+ "grad_norm": 0.21981129050254822,
1818
+ "learning_rate": 1.1365201095496048e-05,
1819
+ "loss": 0.4809,
1820
+ "memory/device_reserved (GiB)": 139.06,
1821
+ "memory/max_active (GiB)": 25.53,
1822
+ "memory/max_allocated (GiB)": 25.53,
1823
+ "ppl": 1.6175,
1824
+ "step": 3400,
1825
+ "tokens_per_second_per_gpu": 4233.11,
1826
+ "total_tokens": 65735025
1827
+ },
1828
+ {
1829
+ "epoch": 2.569392348087022,
1830
+ "grad_norm": 0.22363677620887756,
1831
+ "learning_rate": 1.0449868205649649e-05,
1832
+ "loss": 0.4605,
1833
+ "memory/device_reserved (GiB)": 139.06,
1834
+ "memory/max_active (GiB)": 25.53,
1835
+ "memory/max_allocated (GiB)": 25.53,
1836
+ "ppl": 1.5849,
1837
+ "step": 3425,
1838
+ "tokens_per_second_per_gpu": 4245.88,
1839
+ "total_tokens": 66180426
1840
+ },
1841
+ {
1842
+ "epoch": 2.5881470367591897,
1843
+ "grad_norm": 0.21145139634609222,
1844
+ "learning_rate": 9.570926265363789e-06,
1845
+ "loss": 0.4661,
1846
+ "memory/device_reserved (GiB)": 139.06,
1847
+ "memory/max_active (GiB)": 25.53,
1848
+ "memory/max_allocated (GiB)": 25.53,
1849
+ "ppl": 1.5938,
1850
+ "step": 3450,
1851
+ "tokens_per_second_per_gpu": 4280.85,
1852
+ "total_tokens": 66629602
1853
+ },
1854
+ {
1855
+ "epoch": 2.606901725431358,
1856
+ "grad_norm": 0.2377360314130783,
1857
+ "learning_rate": 8.728732454814203e-06,
1858
+ "loss": 0.46,
1859
+ "memory/device_reserved (GiB)": 139.06,
1860
+ "memory/max_active (GiB)": 25.53,
1861
+ "memory/max_allocated (GiB)": 25.53,
1862
+ "ppl": 1.5841,
1863
+ "step": 3475,
1864
+ "tokens_per_second_per_gpu": 4258.29,
1865
+ "total_tokens": 67075180
1866
+ },
1867
+ {
1868
+ "epoch": 2.625656414103526,
1869
+ "grad_norm": 0.22640903294086456,
1870
+ "learning_rate": 7.923629020649448e-06,
1871
+ "loss": 0.4734,
1872
+ "memory/device_reserved (GiB)": 139.06,
1873
+ "memory/max_active (GiB)": 25.53,
1874
+ "memory/max_allocated (GiB)": 25.53,
1875
+ "ppl": 1.6054,
1876
+ "step": 3500,
1877
+ "tokens_per_second_per_gpu": 3732.79,
1878
+ "total_tokens": 67519655
1879
+ },
1880
+ {
1881
+ "epoch": 2.644411102775694,
1882
+ "grad_norm": 0.2617396414279938,
1883
+ "learning_rate": 7.155943136910193e-06,
1884
+ "loss": 0.4701,
1885
+ "memory/device_reserved (GiB)": 139.06,
1886
+ "memory/max_active (GiB)": 25.53,
1887
+ "memory/max_allocated (GiB)": 25.53,
1888
+ "ppl": 1.6002,
1889
+ "step": 3525,
1890
+ "tokens_per_second_per_gpu": 4208.25,
1891
+ "total_tokens": 67960790
1892
+ },
1893
+ {
1894
+ "epoch": 2.663165791447862,
1895
+ "grad_norm": 0.2119966447353363,
1896
+ "learning_rate": 6.425986772073922e-06,
1897
+ "loss": 0.4754,
1898
+ "memory/device_reserved (GiB)": 139.06,
1899
+ "memory/max_active (GiB)": 25.53,
1900
+ "memory/max_allocated (GiB)": 25.53,
1901
+ "ppl": 1.6087,
1902
+ "step": 3550,
1903
+ "tokens_per_second_per_gpu": 4238.47,
1904
+ "total_tokens": 68405914
1905
+ },
1906
+ {
1907
+ "epoch": 2.68192048012003,
1908
+ "grad_norm": 0.21404898166656494,
1909
+ "learning_rate": 5.734056562278634e-06,
1910
+ "loss": 0.4536,
1911
+ "memory/device_reserved (GiB)": 139.06,
1912
+ "memory/max_active (GiB)": 25.53,
1913
+ "memory/max_allocated (GiB)": 25.53,
1914
+ "ppl": 1.574,
1915
+ "step": 3575,
1916
+ "tokens_per_second_per_gpu": 4293.79,
1917
+ "total_tokens": 68854437
1918
+ },
1919
+ {
1920
+ "epoch": 2.700675168792198,
1921
+ "grad_norm": 0.207435742020607,
1922
+ "learning_rate": 5.080433690777353e-06,
1923
+ "loss": 0.4726,
1924
+ "memory/device_reserved (GiB)": 139.06,
1925
+ "memory/max_active (GiB)": 25.53,
1926
+ "memory/max_allocated (GiB)": 25.53,
1927
+ "ppl": 1.6042,
1928
+ "step": 3600,
1929
+ "tokens_per_second_per_gpu": 4137.98,
1930
+ "total_tokens": 69296241
1931
+ },
1932
+ {
1933
+ "epoch": 2.719429857464366,
1934
+ "grad_norm": 0.23212255537509918,
1935
+ "learning_rate": 4.465383773672127e-06,
1936
+ "loss": 0.4626,
1937
+ "memory/device_reserved (GiB)": 139.06,
1938
+ "memory/max_active (GiB)": 25.53,
1939
+ "memory/max_allocated (GiB)": 25.53,
1940
+ "ppl": 1.5882,
1941
+ "step": 3625,
1942
+ "tokens_per_second_per_gpu": 4195.93,
1943
+ "total_tokens": 69736200
1944
+ },
1945
+ {
1946
+ "epoch": 2.738184546136534,
1947
+ "grad_norm": 0.24078768491744995,
1948
+ "learning_rate": 3.889156751974343e-06,
1949
+ "loss": 0.4652,
1950
+ "memory/device_reserved (GiB)": 139.06,
1951
+ "memory/max_active (GiB)": 25.53,
1952
+ "memory/max_allocated (GiB)": 25.53,
1953
+ "ppl": 1.5923,
1954
+ "step": 3650,
1955
+ "tokens_per_second_per_gpu": 4260.72,
1956
+ "total_tokens": 70181446
1957
+ },
1958
+ {
1959
+ "epoch": 2.7569392348087023,
1960
+ "grad_norm": 0.20761160552501678,
1961
+ "learning_rate": 3.3519867900349113e-06,
1962
+ "loss": 0.4603,
1963
+ "memory/device_reserved (GiB)": 139.06,
1964
+ "memory/max_active (GiB)": 25.53,
1965
+ "memory/max_allocated (GiB)": 25.53,
1966
+ "ppl": 1.5845,
1967
+ "step": 3675,
1968
+ "tokens_per_second_per_gpu": 3783.05,
1969
+ "total_tokens": 70627535
1970
+ },
1971
+ {
1972
+ "epoch": 2.77569392348087,
1973
+ "grad_norm": 0.2079222947359085,
1974
+ "learning_rate": 2.8540921803855926e-06,
1975
+ "loss": 0.459,
1976
+ "memory/device_reserved (GiB)": 139.06,
1977
+ "memory/max_active (GiB)": 25.53,
1978
+ "memory/max_allocated (GiB)": 25.53,
1979
+ "ppl": 1.5825,
1980
+ "step": 3700,
1981
+ "tokens_per_second_per_gpu": 4196.92,
1982
+ "total_tokens": 71068359
1983
+ },
1984
+ {
1985
+ "epoch": 2.7944486121530385,
1986
+ "grad_norm": 0.23349842429161072,
1987
+ "learning_rate": 2.395675255030383e-06,
1988
+ "loss": 0.4692,
1989
+ "memory/device_reserved (GiB)": 139.06,
1990
+ "memory/max_active (GiB)": 25.53,
1991
+ "memory/max_allocated (GiB)": 25.53,
1992
+ "ppl": 1.5987,
1993
+ "step": 3725,
1994
+ "tokens_per_second_per_gpu": 4216.77,
1995
+ "total_tokens": 71509553
1996
+ },
1997
+ {
1998
+ "epoch": 2.813203300825206,
1999
+ "grad_norm": 0.2154284566640854,
2000
+ "learning_rate": 1.9769223032228724e-06,
2001
+ "loss": 0.4626,
2002
+ "memory/device_reserved (GiB)": 139.06,
2003
+ "memory/max_active (GiB)": 25.53,
2004
+ "memory/max_allocated (GiB)": 25.53,
2005
+ "ppl": 1.5882,
2006
+ "step": 3750,
2007
+ "tokens_per_second_per_gpu": 4278.81,
2008
+ "total_tokens": 71956413
2009
+ },
2010
+ {
2011
+ "epoch": 2.8319579894973743,
2012
+ "grad_norm": 0.2559005916118622,
2013
+ "learning_rate": 1.5980034957628231e-06,
2014
+ "loss": 0.4757,
2015
+ "memory/device_reserved (GiB)": 139.06,
2016
+ "memory/max_active (GiB)": 25.53,
2017
+ "memory/max_allocated (GiB)": 25.53,
2018
+ "ppl": 1.6091,
2019
+ "step": 3775,
2020
+ "tokens_per_second_per_gpu": 4161.74,
2021
+ "total_tokens": 72391979
2022
+ },
2023
+ {
2024
+ "epoch": 2.8507126781695424,
2025
+ "grad_norm": 0.21530191600322723,
2026
+ "learning_rate": 1.2590728158430431e-06,
2027
+ "loss": 0.4823,
2028
+ "memory/device_reserved (GiB)": 139.06,
2029
+ "memory/max_active (GiB)": 25.53,
2030
+ "memory/max_allocated (GiB)": 25.53,
2031
+ "ppl": 1.6198,
2032
+ "step": 3800,
2033
+ "tokens_per_second_per_gpu": 4264.41,
2034
+ "total_tokens": 72837687
2035
+ },
2036
+ {
2037
+ "epoch": 2.8694673668417106,
2038
+ "grad_norm": 0.22042331099510193,
2039
+ "learning_rate": 9.602679964744288e-07,
2040
+ "loss": 0.468,
2041
+ "memory/device_reserved (GiB)": 139.06,
2042
+ "memory/max_active (GiB)": 25.53,
2043
+ "memory/max_allocated (GiB)": 25.53,
2044
+ "ppl": 1.5968,
2045
+ "step": 3825,
2046
+ "tokens_per_second_per_gpu": 4254.73,
2047
+ "total_tokens": 73282095
2048
+ },
2049
+ {
2050
+ "epoch": 2.8882220555138787,
2051
+ "grad_norm": 0.22293563187122345,
2052
+ "learning_rate": 7.017104645146599e-07,
2053
+ "loss": 0.4651,
2054
+ "memory/device_reserved (GiB)": 139.06,
2055
+ "memory/max_active (GiB)": 25.53,
2056
+ "memory/max_allocated (GiB)": 25.53,
2057
+ "ppl": 1.5922,
2058
+ "step": 3850,
2059
+ "tokens_per_second_per_gpu": 3747.29,
2060
+ "total_tokens": 73724795
2061
+ },
2062
+ {
2063
+ "epoch": 2.9069767441860463,
2064
+ "grad_norm": 0.20620891451835632,
2065
+ "learning_rate": 4.83505291323405e-07,
2066
+ "loss": 0.4598,
2067
+ "memory/device_reserved (GiB)": 139.06,
2068
+ "memory/max_active (GiB)": 25.53,
2069
+ "memory/max_allocated (GiB)": 25.53,
2070
+ "ppl": 1.5838,
2071
+ "step": 3875,
2072
+ "tokens_per_second_per_gpu": 4202.85,
2073
+ "total_tokens": 74165185
2074
+ },
2075
+ {
2076
+ "epoch": 2.9257314328582145,
2077
+ "grad_norm": 0.21627213060855865,
2078
+ "learning_rate": 3.0574115006383185e-07,
2079
+ "loss": 0.4713,
2080
+ "memory/device_reserved (GiB)": 139.06,
2081
+ "memory/max_active (GiB)": 25.53,
2082
+ "memory/max_allocated (GiB)": 25.53,
2083
+ "ppl": 1.6021,
2084
+ "step": 3900,
2085
+ "tokens_per_second_per_gpu": 4239.36,
2086
+ "total_tokens": 74606090
2087
+ },
2088
+ {
2089
+ "epoch": 2.9444861215303826,
2090
+ "grad_norm": 0.22113533318042755,
2091
+ "learning_rate": 1.6849027966816532e-07,
2092
+ "loss": 0.4893,
2093
+ "memory/device_reserved (GiB)": 139.06,
2094
+ "memory/max_active (GiB)": 25.53,
2095
+ "memory/max_allocated (GiB)": 25.53,
2096
+ "ppl": 1.6312,
2097
+ "step": 3925,
2098
+ "tokens_per_second_per_gpu": 4207.44,
2099
+ "total_tokens": 75045579
2100
+ },
2101
+ {
2102
+ "epoch": 2.9632408102025507,
2103
+ "grad_norm": 0.21696196496486664,
2104
+ "learning_rate": 7.180845548145909e-08,
2105
+ "loss": 0.4804,
2106
+ "memory/device_reserved (GiB)": 139.06,
2107
+ "memory/max_active (GiB)": 25.53,
2108
+ "memory/max_allocated (GiB)": 25.53,
2109
+ "ppl": 1.6167,
2110
+ "step": 3950,
2111
+ "tokens_per_second_per_gpu": 4152.94,
2112
+ "total_tokens": 75479895
2113
+ },
2114
+ {
2115
+ "epoch": 2.981995498874719,
2116
+ "grad_norm": 0.2239820659160614,
2117
+ "learning_rate": 1.5734966595948308e-08,
2118
+ "loss": 0.4758,
2119
+ "memory/device_reserved (GiB)": 139.06,
2120
+ "memory/max_active (GiB)": 25.53,
2121
+ "memory/max_allocated (GiB)": 25.53,
2122
+ "ppl": 1.6093,
2123
+ "step": 3975,
2124
+ "tokens_per_second_per_gpu": 4224.58,
2125
+ "total_tokens": 75920694
2126
+ }
2127
+ ],
2128
+ "logging_steps": 25,
2129
+ "max_steps": 3996,
2130
+ "num_input_tokens_seen": 0,
2131
+ "num_train_epochs": 3,
2132
+ "save_steps": 1000,
2133
+ "stateful_callbacks": {
2134
+ "TrainerControl": {
2135
+ "args": {
2136
+ "should_epoch_stop": false,
2137
+ "should_evaluate": false,
2138
+ "should_log": false,
2139
+ "should_save": true,
2140
+ "should_training_stop": true
2141
+ },
2142
+ "attributes": {}
2143
+ }
2144
+ },
2145
+ "total_flos": 3.2526641635157606e+18,
2146
+ "train_batch_size": 5,
2147
+ "trial_name": null,
2148
+ "trial_params": null
2149
+ }
checkpoint-3996/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a75cafa9afe18e1aa48e766453f03add03ceb5dd78011703e6068968ae04eab2
3
+ size 7761
debug.log CHANGED
The diff for this file is too large to render. See raw diff