DeepDream2045 commited on
Commit
7f4e693
1 Parent(s): 40f22ed

End of training

Browse files
Files changed (2) hide show
  1. README.md +152 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,152 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4
4
+ tags:
5
+ - axolotl
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: 8818eebe-3505-4b30-8d5c-72c319b17bab
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: `0.5.2`
19
+ ```yaml
20
+ adapter: lora
21
+ base_model: MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4
22
+ bf16: auto
23
+ chat_template: llama3
24
+ dataset_prepared_path: null
25
+ datasets:
26
+ - data_files:
27
+ - f3058a58b1f571da_train_data.json
28
+ ds_type: json
29
+ format: custom
30
+ path: /workspace/input_data/f3058a58b1f571da_train_data.json
31
+ type:
32
+ field_instruction: question
33
+ field_output: answers
34
+ format: '{instruction}'
35
+ no_input_format: '{instruction}'
36
+ system_format: '{system}'
37
+ system_prompt: ''
38
+ debug: null
39
+ deepspeed: null
40
+ early_stopping_patience: 1
41
+ eval_max_new_tokens: 128
42
+ eval_steps: 25
43
+ eval_table_size: null
44
+ flash_attention: false
45
+ fp16: false
46
+ fsdp: null
47
+ fsdp_config: null
48
+ gradient_accumulation_steps: 16
49
+ gradient_checkpointing: true
50
+ group_by_length: true
51
+ hub_model_id: DeepDream2045/8818eebe-3505-4b30-8d5c-72c319b17bab
52
+ hub_repo: null
53
+ hub_strategy: checkpoint
54
+ hub_token: null
55
+ learning_rate: 0.0001
56
+ load_in_4bit: false
57
+ load_in_8bit: false
58
+ local_rank: null
59
+ logging_steps: 1
60
+ lora_alpha: 64
61
+ lora_dropout: 0.05
62
+ lora_fan_in_fan_out: null
63
+ lora_model_dir: null
64
+ lora_r: 32
65
+ lora_target_linear: true
66
+ lr_scheduler: cosine
67
+ max_steps: 50
68
+ micro_batch_size: 2
69
+ mlflow_experiment_name: /tmp/f3058a58b1f571da_train_data.json
70
+ model_type: AutoModelForCausalLM
71
+ num_epochs: 3
72
+ optimizer: adamw_torch
73
+ output_dir: miner_id_24
74
+ pad_to_sequence_len: true
75
+ resume_from_checkpoint: null
76
+ s2_attention: null
77
+ sample_packing: false
78
+ save_steps: 25
79
+ sequence_len: 2048
80
+ strict: false
81
+ tf32: false
82
+ tokenizer_type: AutoTokenizer
83
+ train_on_inputs: false
84
+ trust_remote_code: true
85
+ val_set_size: 0.05
86
+ wandb_entity: null
87
+ wandb_mode: online
88
+ wandb_name: 8818eebe-3505-4b30-8d5c-72c319b17bab
89
+ wandb_project: Gradients-On-Demand
90
+ wandb_run: your_name
91
+ wandb_runid: 8818eebe-3505-4b30-8d5c-72c319b17bab
92
+ warmup_ratio: 0.05
93
+ weight_decay: 0.01
94
+ xformers_attention: true
95
+
96
+ ```
97
+
98
+ </details><br>
99
+
100
+ # 8818eebe-3505-4b30-8d5c-72c319b17bab
101
+
102
+ This model is a fine-tuned version of [MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4](https://huggingface.co/MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4) on the None dataset.
103
+ It achieves the following results on the evaluation set:
104
+ - Loss: 0.6490
105
+
106
+ ## Model description
107
+
108
+ More information needed
109
+
110
+ ## Intended uses & limitations
111
+
112
+ More information needed
113
+
114
+ ## Training and evaluation data
115
+
116
+ More information needed
117
+
118
+ ## Training procedure
119
+
120
+ ### Training hyperparameters
121
+
122
+ The following hyperparameters were used during training:
123
+ - learning_rate: 0.0001
124
+ - train_batch_size: 2
125
+ - eval_batch_size: 2
126
+ - seed: 42
127
+ - distributed_type: multi-GPU
128
+ - num_devices: 4
129
+ - gradient_accumulation_steps: 16
130
+ - total_train_batch_size: 128
131
+ - total_eval_batch_size: 8
132
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
133
+ - lr_scheduler_type: cosine
134
+ - lr_scheduler_warmup_steps: 2
135
+ - training_steps: 50
136
+
137
+ ### Training results
138
+
139
+ | Training Loss | Epoch | Step | Validation Loss |
140
+ |:-------------:|:------:|:----:|:---------------:|
141
+ | 1.5723 | 0.0258 | 1 | 4.0140 |
142
+ | 0.4878 | 0.6462 | 25 | 0.6940 |
143
+ | 0.7053 | 1.3021 | 50 | 0.6490 |
144
+
145
+
146
+ ### Framework versions
147
+
148
+ - PEFT 0.13.2
149
+ - Transformers 4.46.3
150
+ - Pytorch 2.3.1+cu121
151
+ - Datasets 3.1.0
152
+ - Tokenizers 0.20.3
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fbae9045cd92690146e532e542f5b0a39b6f32694344e01b3e53b874fc3fcfca
3
+ size 860011282