eeeebbb2 commited on
Commit
ed8053a
1 Parent(s): f4b55eb

End of training

Browse files
Files changed (2) hide show
  1. README.md +173 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,173 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: NousResearch/Yarn-Llama-2-7b-128k
4
+ tags:
5
+ - axolotl
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: a8875a95-a87f-4fb5-a7c2-215272809544
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ [<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)
16
+ <details><summary>See axolotl config</summary>
17
+
18
+ axolotl version: `0.4.1`
19
+ ```yaml
20
+ adapter: lora
21
+ base_model: NousResearch/Yarn-Llama-2-7b-128k
22
+ bf16: auto
23
+ chat_template: llama3
24
+ cosine_min_lr_ratio: 0.1
25
+ data_processes: 4
26
+ dataset_prepared_path: null
27
+ datasets:
28
+ - data_files:
29
+ - 536825f84ab6c1ab_train_data.json
30
+ ds_type: json
31
+ format: custom
32
+ num_proc: 4
33
+ path: /workspace/input_data/536825f84ab6c1ab_train_data.json
34
+ streaming: true
35
+ type:
36
+ field_instruction: instruction
37
+ field_output: output
38
+ format: '{instruction}'
39
+ no_input_format: '{instruction}'
40
+ system_format: '{system}'
41
+ system_prompt: ''
42
+ debug: null
43
+ deepspeed: null
44
+ device_map: balanced
45
+ do_eval: true
46
+ early_stopping_patience: 1
47
+ eval_batch_size: 1
48
+ eval_sample_packing: false
49
+ eval_steps: 25
50
+ evaluation_strategy: steps
51
+ flash_attention: false
52
+ fp16: null
53
+ fsdp: null
54
+ fsdp_config: null
55
+ gradient_accumulation_steps: 16
56
+ gradient_checkpointing: true
57
+ group_by_length: true
58
+ hub_model_id: eeeebbb2/a8875a95-a87f-4fb5-a7c2-215272809544
59
+ hub_strategy: checkpoint
60
+ hub_token: null
61
+ learning_rate: 0.0001
62
+ load_in_4bit: false
63
+ load_in_8bit: false
64
+ local_rank: null
65
+ logging_steps: 1
66
+ lora_alpha: 64
67
+ lora_dropout: 0.05
68
+ lora_fan_in_fan_out: null
69
+ lora_model_dir: null
70
+ lora_r: 32
71
+ lora_target_linear: true
72
+ lora_target_modules:
73
+ - q_proj
74
+ - v_proj
75
+ lr_scheduler: cosine
76
+ max_grad_norm: 1.0
77
+ max_memory:
78
+ 0: 75GB
79
+ 1: 75GB
80
+ 2: 75GB
81
+ 3: 75GB
82
+ max_steps: 50
83
+ micro_batch_size: 2
84
+ mixed_precision: bf16
85
+ mlflow_experiment_name: /tmp/536825f84ab6c1ab_train_data.json
86
+ model_type: AutoModelForCausalLM
87
+ num_epochs: 3
88
+ optim_args:
89
+ adam_beta1: 0.9
90
+ adam_beta2: 0.95
91
+ adam_epsilon: 1e-5
92
+ optimizer: adamw_torch
93
+ output_dir: miner_id_24
94
+ pad_to_sequence_len: true
95
+ resume_from_checkpoint: null
96
+ s2_attention: null
97
+ sample_packing: false
98
+ save_steps: 25
99
+ save_strategy: steps
100
+ sequence_len: 2048
101
+ strict: false
102
+ tf32: false
103
+ tokenizer_type: AutoTokenizer
104
+ torch_compile: false
105
+ train_on_inputs: false
106
+ trust_remote_code: true
107
+ val_set_size: 50
108
+ wandb_entity: null
109
+ wandb_mode: online
110
+ wandb_name: a8875a95-a87f-4fb5-a7c2-215272809544
111
+ wandb_project: Public_TuningSN
112
+ wandb_runid: a8875a95-a87f-4fb5-a7c2-215272809544
113
+ warmup_ratio: 0.04
114
+ weight_decay: 0.01
115
+ xformers_attention: null
116
+
117
+ ```
118
+
119
+ </details><br>
120
+
121
+ # a8875a95-a87f-4fb5-a7c2-215272809544
122
+
123
+ This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-7b-128k](https://huggingface.co/NousResearch/Yarn-Llama-2-7b-128k) on the None dataset.
124
+ It achieves the following results on the evaluation set:
125
+ - Loss: 1.5879
126
+
127
+ ## Model description
128
+
129
+ More information needed
130
+
131
+ ## Intended uses & limitations
132
+
133
+ More information needed
134
+
135
+ ## Training and evaluation data
136
+
137
+ More information needed
138
+
139
+ ## Training procedure
140
+
141
+ ### Training hyperparameters
142
+
143
+ The following hyperparameters were used during training:
144
+ - learning_rate: 0.0001
145
+ - train_batch_size: 2
146
+ - eval_batch_size: 1
147
+ - seed: 42
148
+ - distributed_type: multi-GPU
149
+ - num_devices: 4
150
+ - gradient_accumulation_steps: 16
151
+ - total_train_batch_size: 128
152
+ - total_eval_batch_size: 4
153
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
154
+ - lr_scheduler_type: cosine
155
+ - lr_scheduler_warmup_steps: 2
156
+ - training_steps: 50
157
+
158
+ ### Training results
159
+
160
+ | Training Loss | Epoch | Step | Validation Loss |
161
+ |:-------------:|:------:|:----:|:---------------:|
162
+ | 25.6742 | 0.0025 | 1 | 2.1383 |
163
+ | 29.4658 | 0.0623 | 25 | 1.6877 |
164
+ | 26.3377 | 0.1246 | 50 | 1.5879 |
165
+
166
+
167
+ ### Framework versions
168
+
169
+ - PEFT 0.13.2
170
+ - Transformers 4.46.0
171
+ - Pytorch 2.5.0+cu124
172
+ - Datasets 3.0.1
173
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f849ad3a40b7ae02eb3906be82f230b8f05502a8668fa9f372d8921587c2d75e
3
+ size 319977674