tryingpro commited on
Commit
aaa28a2
·
verified ·
1 Parent(s): b40b105

End of training

Browse files
Files changed (2) hide show
  1. README.md +165 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,165 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: llama3
4
+ base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
5
+ tags:
6
+ - axolotl
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: 993e9431-d73f-4b94-b139-72a7f8db89e8
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ [<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)
17
+ <details><summary>See axolotl config</summary>
18
+
19
+ axolotl version: `0.4.1`
20
+ ```yaml
21
+ adapter: lora
22
+ base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
23
+ bf16: auto
24
+ chat_template: llama3
25
+ dataset_prepared_path: null
26
+ datasets:
27
+ - data_files:
28
+ - 3acd96c57ed25104_train_data.json
29
+ ds_type: json
30
+ format: custom
31
+ path: /workspace/input_data/3acd96c57ed25104_train_data.json
32
+ type:
33
+ field_instruction: script
34
+ field_output: summary
35
+ format: '{instruction}'
36
+ no_input_format: '{instruction}'
37
+ system_format: '{system}'
38
+ system_prompt: ''
39
+ debug: null
40
+ deepspeed: null
41
+ early_stopping_patience: null
42
+ eval_max_new_tokens: 256
43
+ eval_steps: 25
44
+ eval_table_size: null
45
+ evals_per_epoch: null
46
+ flash_attention: false
47
+ fp16: null
48
+ fsdp: null
49
+ fsdp_config: null
50
+ gradient_accumulation_steps: 32
51
+ gradient_checkpointing: true
52
+ group_by_length: false
53
+ hub_model_id: tryingpro/993e9431-d73f-4b94-b139-72a7f8db89e8
54
+ hub_repo: null
55
+ hub_strategy: checkpoint
56
+ hub_token: null
57
+ learning_rate: 0.0002
58
+ load_in_4bit: false
59
+ load_in_8bit: false
60
+ local_rank: null
61
+ logging_steps: 1
62
+ lora_alpha: 64
63
+ lora_dropout: 0.05
64
+ lora_fan_in_fan_out: null
65
+ lora_model_dir: null
66
+ lora_r: 32
67
+ lora_target_linear: true
68
+ lora_target_modules:
69
+ - q_proj
70
+ - k_proj
71
+ - v_proj
72
+ - o_proj
73
+ - gate_proj
74
+ - down_proj
75
+ - up_proj
76
+ lr_scheduler: cosine
77
+ max_grad_norm: 2
78
+ max_steps: 125
79
+ micro_batch_size: 2
80
+ mlflow_experiment_name: /tmp/3acd96c57ed25104_train_data.json
81
+ model_type: AutoModelForCausalLM
82
+ num_epochs: 3
83
+ optim_args:
84
+ adam_beta1: 0.9
85
+ adam_beta2: 0.95
86
+ adam_epsilon: 1.0e-05
87
+ optimizer: adamw_torch
88
+ output_dir: miner_id_24
89
+ pad_to_sequence_len: true
90
+ resume_from_checkpoint: null
91
+ s2_attention: null
92
+ sample_packing: false
93
+ saves_per_epoch: 4
94
+ sequence_len: 2048
95
+ strict: false
96
+ tf32: false
97
+ tokenizer_type: AutoTokenizer
98
+ train_on_inputs: false
99
+ trust_remote_code: true
100
+ val_set_size: 0.05
101
+ wandb_entity: tryingpro-unicourt
102
+ wandb_mode: online
103
+ wandb_name: 6499fe58-ad98-45f1-bb10-b4342e2c5302
104
+ wandb_project: Gradients-On-Demand
105
+ wandb_run: your_name
106
+ wandb_runid: 6499fe58-ad98-45f1-bb10-b4342e2c5302
107
+ warmup_steps: 20
108
+ weight_decay: 0.02
109
+ xformers_attention: false
110
+
111
+ ```
112
+
113
+ </details><br>
114
+
115
+ # 993e9431-d73f-4b94-b139-72a7f8db89e8
116
+
117
+ This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset.
118
+ It achieves the following results on the evaluation set:
119
+ - Loss: 2.1104
120
+
121
+ ## Model description
122
+
123
+ More information needed
124
+
125
+ ## Intended uses & limitations
126
+
127
+ More information needed
128
+
129
+ ## Training and evaluation data
130
+
131
+ More information needed
132
+
133
+ ## Training procedure
134
+
135
+ ### Training hyperparameters
136
+
137
+ The following hyperparameters were used during training:
138
+ - learning_rate: 0.0002
139
+ - train_batch_size: 2
140
+ - eval_batch_size: 2
141
+ - seed: 42
142
+ - gradient_accumulation_steps: 32
143
+ - total_train_batch_size: 64
144
+ - 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-05
145
+ - lr_scheduler_type: cosine
146
+ - lr_scheduler_warmup_steps: 20
147
+ - training_steps: 90
148
+
149
+ ### Training results
150
+
151
+ | Training Loss | Epoch | Step | Validation Loss |
152
+ |:-------------:|:------:|:----:|:---------------:|
153
+ | 2.1869 | 0.0337 | 1 | 2.1871 |
154
+ | 2.1273 | 0.8421 | 25 | 2.0857 |
155
+ | 2.0096 | 1.6947 | 50 | 2.0875 |
156
+ | 1.8257 | 2.5474 | 75 | 2.1104 |
157
+
158
+
159
+ ### Framework versions
160
+
161
+ - PEFT 0.13.2
162
+ - Transformers 4.46.0
163
+ - Pytorch 2.5.0+cu124
164
+ - Datasets 3.0.1
165
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7db7b42544d9f400bc8a11a4b235ec7a2a90fbbd7c6756d9b70ac32de30a2d23
3
+ size 335706186