mamung commited on
Commit
16f26aa
·
verified ·
1 Parent(s): a48cfe8

End of training

Browse files
Files changed (2) hide show
  1. README.md +170 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,170 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: 25a33e11-6aee-4ba0-98a3-3329318b5c77
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: true
24
+ chat_template: llama3
25
+ dataset_prepared_path: null
26
+ datasets:
27
+ - data_files:
28
+ - cb755dbfd59bc042_train_data.json
29
+ ds_type: json
30
+ format: custom
31
+ path: /workspace/input_data/cb755dbfd59bc042_train_data.json
32
+ type:
33
+ field_input: ''
34
+ field_instruction: prompt
35
+ field_output: answer
36
+ format: '{instruction}'
37
+ no_input_format: '{instruction}'
38
+ system_format: '{system}'
39
+ system_prompt: ''
40
+ debug: null
41
+ deepspeed: null
42
+ early_stopping_patience: null
43
+ eval_max_new_tokens: 256
44
+ eval_table_size: null
45
+ evals_per_epoch: 4
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: mamung/25a33e11-6aee-4ba0-98a3-3329318b5c77
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: 3
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
+ lr_scheduler: cosine
74
+ max_grad_norm: 2
75
+ max_steps: 100
76
+ micro_batch_size: 2
77
+ mlflow_experiment_name: /tmp/cb755dbfd59bc042_train_data.json
78
+ model_type: AutoModelForCausalLM
79
+ num_epochs: 3
80
+ optim_args:
81
+ adam_beta1: 0.9
82
+ adam_beta2: 0.95
83
+ adam_epsilon: 1.0e-05
84
+ optimizer: adamw_torch
85
+ output_dir: miner_id_24
86
+ pad_to_sequence_len: true
87
+ resume_from_checkpoint: null
88
+ s2_attention: null
89
+ sample_packing: false
90
+ saves_per_epoch: 4
91
+ sequence_len: 2048
92
+ strict: false
93
+ tf32: false
94
+ tokenizer_type: AutoTokenizer
95
+ train_on_inputs: false
96
+ trust_remote_code: true
97
+ val_set_size: 0.05
98
+ wandb_entity: eddysang
99
+ wandb_mode: online
100
+ wandb_name: 5e080b58-8e49-4fa2-b005-5247717cba1b
101
+ wandb_project: Gradients-On-Demand
102
+ wandb_run: your_name
103
+ wandb_runid: 5e080b58-8e49-4fa2-b005-5247717cba1b
104
+ warmup_steps: 20
105
+ weight_decay: 0.02
106
+ xformers_attention: false
107
+
108
+ ```
109
+
110
+ </details><br>
111
+
112
+ # 25a33e11-6aee-4ba0-98a3-3329318b5c77
113
+
114
+ 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.
115
+ It achieves the following results on the evaluation set:
116
+ - Loss: 1.0599
117
+
118
+ ## Model description
119
+
120
+ More information needed
121
+
122
+ ## Intended uses & limitations
123
+
124
+ More information needed
125
+
126
+ ## Training and evaluation data
127
+
128
+ More information needed
129
+
130
+ ## Training procedure
131
+
132
+ ### Training hyperparameters
133
+
134
+ The following hyperparameters were used during training:
135
+ - learning_rate: 0.0002
136
+ - train_batch_size: 2
137
+ - eval_batch_size: 2
138
+ - seed: 42
139
+ - gradient_accumulation_steps: 32
140
+ - total_train_batch_size: 64
141
+ - 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
142
+ - lr_scheduler_type: cosine
143
+ - lr_scheduler_warmup_steps: 20
144
+ - training_steps: 100
145
+
146
+ ### Training results
147
+
148
+ | Training Loss | Epoch | Step | Validation Loss |
149
+ |:-------------:|:------:|:----:|:---------------:|
150
+ | No log | 0.0024 | 1 | 3.2281 |
151
+ | 1.9405 | 0.0216 | 9 | 1.9358 |
152
+ | 1.5861 | 0.0433 | 18 | 1.4582 |
153
+ | 1.5059 | 0.0649 | 27 | 1.3450 |
154
+ | 1.4494 | 0.0865 | 36 | 1.2606 |
155
+ | 1.3834 | 0.1082 | 45 | 1.1997 |
156
+ | 1.1531 | 0.1298 | 54 | 1.1465 |
157
+ | 1.1702 | 0.1515 | 63 | 1.1220 |
158
+ | 1.2195 | 0.1731 | 72 | 1.0894 |
159
+ | 1.237 | 0.1947 | 81 | 1.0702 |
160
+ | 1.1906 | 0.2164 | 90 | 1.0622 |
161
+ | 1.117 | 0.2380 | 99 | 1.0599 |
162
+
163
+
164
+ ### Framework versions
165
+
166
+ - PEFT 0.13.2
167
+ - Transformers 4.46.0
168
+ - Pytorch 2.5.0+cu124
169
+ - Datasets 3.0.1
170
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:989b682bc77a895a214671268c8885a1b881620047a721ec96950d9d6605a67b
3
+ size 335706186