nttx commited on
Commit
b18cae9
1 Parent(s): e51fb0b

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
+ base_model: HuggingFaceH4/tiny-random-LlamaForCausalLM
4
+ tags:
5
+ - axolotl
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: 2846e477-17ed-4d4a-8598-8e074fe642b9
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: HuggingFaceH4/tiny-random-LlamaForCausalLM
22
+ bf16: true
23
+ chat_template: llama3
24
+ data_processes: 16
25
+ dataset_prepared_path: null
26
+ datasets:
27
+ - data_files:
28
+ - 5f82ee8703e0bca6_train_data.json
29
+ ds_type: json
30
+ format: custom
31
+ path: /workspace/input_data/5f82ee8703e0bca6_train_data.json
32
+ type:
33
+ field_input: Type
34
+ field_instruction: Prompt
35
+ field_output: BetterCompletion
36
+ format: '{instruction} {input}'
37
+ no_input_format: '{instruction}'
38
+ system_format: '{system}'
39
+ system_prompt: ''
40
+ debug: null
41
+ deepspeed: null
42
+ device_map: auto
43
+ do_eval: true
44
+ early_stopping_patience: 5
45
+ eval_batch_size: 4
46
+ eval_max_new_tokens: 128
47
+ eval_steps: 50
48
+ eval_table_size: null
49
+ evals_per_epoch: null
50
+ flash_attention: false
51
+ fp16: false
52
+ fsdp: null
53
+ fsdp_config: null
54
+ gradient_accumulation_steps: 8
55
+ gradient_checkpointing: true
56
+ group_by_length: true
57
+ hub_model_id: nttx/2846e477-17ed-4d4a-8598-8e074fe642b9
58
+ hub_repo: null
59
+ hub_strategy: checkpoint
60
+ hub_token: null
61
+ learning_rate: 5.0e-06
62
+ load_in_4bit: false
63
+ load_in_8bit: false
64
+ local_rank: null
65
+ logging_steps: 1
66
+ lora_alpha: 32
67
+ lora_dropout: 0.1
68
+ lora_fan_in_fan_out: null
69
+ lora_model_dir: null
70
+ lora_r: 16
71
+ lora_target_linear: true
72
+ lr_scheduler: cosine
73
+ max_grad_norm: 2.0
74
+ max_memory:
75
+ 0: 70GB
76
+ max_steps: 100
77
+ micro_batch_size: 4
78
+ mlflow_experiment_name: /tmp/5f82ee8703e0bca6_train_data.json
79
+ model_type: AutoModelForCausalLM
80
+ num_epochs: 3
81
+ optim_args:
82
+ adam_beta1: 0.9
83
+ adam_beta2: 0.95
84
+ adam_epsilon: 1e-5
85
+ optimizer: adamw_torch
86
+ output_dir: miner_id_24
87
+ pad_to_sequence_len: true
88
+ resume_from_checkpoint: null
89
+ s2_attention: null
90
+ sample_packing: false
91
+ save_steps: 50
92
+ saves_per_epoch: null
93
+ sequence_len: 1024
94
+ special_tokens:
95
+ pad_token: </s>
96
+ strict: false
97
+ tf32: true
98
+ tokenizer_type: AutoTokenizer
99
+ train_on_inputs: false
100
+ trust_remote_code: true
101
+ val_set_size: 0.05
102
+ wandb_entity: null
103
+ wandb_mode: online
104
+ wandb_name: 2846e477-17ed-4d4a-8598-8e074fe642b9
105
+ wandb_project: Gradients-On-Demand
106
+ wandb_run: your_name
107
+ wandb_runid: 2846e477-17ed-4d4a-8598-8e074fe642b9
108
+ warmup_steps: 10
109
+ weight_decay: 0.0
110
+ xformers_attention: null
111
+
112
+ ```
113
+
114
+ </details><br>
115
+
116
+ # 2846e477-17ed-4d4a-8598-8e074fe642b9
117
+
118
+ This model is a fine-tuned version of [HuggingFaceH4/tiny-random-LlamaForCausalLM](https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForCausalLM) on the None dataset.
119
+ It achieves the following results on the evaluation set:
120
+ - Loss: 10.3669
121
+
122
+ ## Model description
123
+
124
+ More information needed
125
+
126
+ ## Intended uses & limitations
127
+
128
+ More information needed
129
+
130
+ ## Training and evaluation data
131
+
132
+ More information needed
133
+
134
+ ## Training procedure
135
+
136
+ ### Training hyperparameters
137
+
138
+ The following hyperparameters were used during training:
139
+ - learning_rate: 5e-06
140
+ - train_batch_size: 4
141
+ - eval_batch_size: 4
142
+ - seed: 42
143
+ - gradient_accumulation_steps: 8
144
+ - total_train_batch_size: 32
145
+ - 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
146
+ - lr_scheduler_type: cosine
147
+ - lr_scheduler_warmup_steps: 10
148
+ - training_steps: 100
149
+
150
+ ### Training results
151
+
152
+ | Training Loss | Epoch | Step | Validation Loss |
153
+ |:-------------:|:------:|:----:|:---------------:|
154
+ | 10.3767 | 0.0176 | 1 | 10.3671 |
155
+ | 10.3707 | 0.8791 | 50 | 10.3670 |
156
+ | 10.2925 | 1.7648 | 100 | 10.3669 |
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:d041baa5fe8c3e7d8317fab4062b34f117c8f7ea3fdc268e5b8e49872a234982
3
+ size 57218