cwaud commited on
Commit
331a22a
1 Parent(s): 632e9c7

End of training

Browse files
Files changed (2) hide show
  1. README.md +164 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,164 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: llama3.1
4
+ base_model: unsloth/Meta-Llama-3.1-8B
5
+ tags:
6
+ - axolotl
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: f5fd42be-f8cb-4dca-b32f-c0b597a2d94b
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: unsloth/Meta-Llama-3.1-8B
23
+ bf16: true
24
+ bnb_config_kwargs:
25
+ bnb_4bit_quant_type: nf4
26
+ bnb_4bit_use_double_quant: true
27
+ chat_template: llama3
28
+ cosine_min_lr_ratio: 0.1
29
+ data_processes: 16
30
+ dataset_prepared_path: null
31
+ datasets:
32
+ - data_files:
33
+ - dialogsum_train_data.json
34
+ ds_type: json
35
+ path: /workspace/input_data/dialogsum_train_data.json
36
+ type:
37
+ field_input: dialogue
38
+ field_instruction: topic
39
+ field_output: summary
40
+ system_format: '{system}'
41
+ system_prompt: ''
42
+ debug: null
43
+ deepspeed: null
44
+ device_map:
45
+ ? ''
46
+ : cuda:0
47
+ do_eval: false
48
+ early_stopping_patience: null
49
+ eval_batch_size: 2
50
+ eval_sample_packing: false
51
+ eval_steps: 0
52
+ evaluation_strategy: 'no'
53
+ flash_attention: true
54
+ fp16: null
55
+ fsdp: null
56
+ fsdp_config: null
57
+ gradient_accumulation_steps: 32
58
+ gradient_checkpointing: true
59
+ group_by_length: true
60
+ hub_model_id: cwaud/f5fd42be-f8cb-4dca-b32f-c0b597a2d94b
61
+ hub_repo: cwaud
62
+ hub_strategy: checkpoint
63
+ hub_token: null
64
+ learning_rate: 0.0001
65
+ load_in_4bit: false
66
+ load_in_8bit: false
67
+ local_rank: null
68
+ logging_steps: 1
69
+ lora_alpha: 64
70
+ lora_dropout: 0.05
71
+ lora_fan_in_fan_out: null
72
+ lora_model_dir: null
73
+ lora_r: 32
74
+ lora_target_linear: true
75
+ lora_target_modules:
76
+ - q_proj
77
+ - v_proj
78
+ lr_scheduler: cosine
79
+ max_grad_norm: 1.0
80
+ max_memory:
81
+ 0: 76GiB
82
+ max_steps: 360
83
+ micro_batch_size: 2
84
+ mlflow_experiment_name: /tmp/dialogsum_train_data.json
85
+ model_type: UnknownForCausalLM
86
+ num_epochs: 4
87
+ optim_args:
88
+ adam_beta1: 0.9
89
+ adam_beta2: 0.95
90
+ adam_epsilon: 1e-5
91
+ optimizer: adamw_bnb_8bit
92
+ output_dir: miner_id_24
93
+ pad_to_sequence_len: true
94
+ resume_from_checkpoint: null
95
+ s2_attention: null
96
+ sample_packing: false
97
+ save_strategy: epoch
98
+ sequence_len: 2048
99
+ strict: false
100
+ tf32: false
101
+ tokenizer_type: AutoTokenizer
102
+ torch_compile: false
103
+ train_on_inputs: false
104
+ val_set_size: 50
105
+ wandb_entity: rayonlabs-rayon-labs
106
+ wandb_mode: online
107
+ wandb_project: Public_TuningSN
108
+ wandb_run: miner_id_24
109
+ wandb_runid: f5fd42be-f8cb-4dca-b32f-c0b597a2d94b
110
+ warmup_raio: 0.03
111
+ warmup_ratio: 0.05
112
+ weight_decay: 0.01
113
+ xformers_attention: null
114
+
115
+ ```
116
+
117
+ </details><br>
118
+
119
+ # f5fd42be-f8cb-4dca-b32f-c0b597a2d94b
120
+
121
+ This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) on the None dataset.
122
+
123
+ ## Model description
124
+
125
+ More information needed
126
+
127
+ ## Intended uses & limitations
128
+
129
+ More information needed
130
+
131
+ ## Training and evaluation data
132
+
133
+ More information needed
134
+
135
+ ## Training procedure
136
+
137
+ ### Training hyperparameters
138
+
139
+ The following hyperparameters were used during training:
140
+ - learning_rate: 0.0001
141
+ - train_batch_size: 2
142
+ - eval_batch_size: 2
143
+ - seed: 42
144
+ - distributed_type: multi-GPU
145
+ - num_devices: 4
146
+ - gradient_accumulation_steps: 32
147
+ - total_train_batch_size: 256
148
+ - total_eval_batch_size: 8
149
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
150
+ - lr_scheduler_type: cosine
151
+ - lr_scheduler_warmup_steps: 11
152
+ - training_steps: 224
153
+
154
+ ### Training results
155
+
156
+
157
+
158
+ ### Framework versions
159
+
160
+ - PEFT 0.13.2
161
+ - Transformers 4.45.2
162
+ - Pytorch 2.4.1+cu124
163
+ - Datasets 3.0.1
164
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ec708eeb8891ae1e1b95debfb00fe1a31f9ee43a760847e2a882d4c936128970
3
+ size 335706186