0x1202 commited on
Commit
16458dc
1 Parent(s): de66d38

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
+ base_model: NousResearch/CodeLlama-7b-hf-flash
4
+ tags:
5
+ - axolotl
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: 769f6c0e-9a41-483a-919d-9e4828a1a4a0
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: NousResearch/CodeLlama-7b-hf-flash
22
+ bf16: auto
23
+ chat_template: llama3
24
+ data_processes: 16
25
+ dataset_prepared_path: null
26
+ datasets:
27
+ - data_files:
28
+ - d191cc991f4fa8fd_train_data.json
29
+ ds_type: json
30
+ format: custom
31
+ path: /workspace/input_data/d191cc991f4fa8fd_train_data.json
32
+ type:
33
+ field_instruction: query
34
+ field_output: response
35
+ format: '{instruction}'
36
+ no_input_format: '{instruction}'
37
+ system_format: '{system}'
38
+ system_prompt: ''
39
+ debug: null
40
+ deepspeed: null
41
+ device_map: auto
42
+ do_eval: true
43
+ early_stopping_patience: 1
44
+ eval_batch_size: 1
45
+ eval_max_new_tokens: 128
46
+ eval_steps: 25
47
+ eval_table_size: null
48
+ evals_per_epoch: null
49
+ flash_attention: false
50
+ fp16: null
51
+ fsdp: null
52
+ fsdp_config: null
53
+ gradient_accumulation_steps: 32
54
+ gradient_checkpointing: true
55
+ group_by_length: true
56
+ hub_model_id: 0x1202/769f6c0e-9a41-483a-919d-9e4828a1a4a0
57
+ hub_repo: null
58
+ hub_strategy: checkpoint
59
+ hub_token: null
60
+ learning_rate: 0.0003
61
+ load_in_4bit: false
62
+ load_in_8bit: false
63
+ local_rank: null
64
+ logging_steps: 1
65
+ lora_alpha: 32
66
+ lora_dropout: 0.05
67
+ lora_fan_in_fan_out: null
68
+ lora_model_dir: null
69
+ lora_r: 16
70
+ lora_target_linear: true
71
+ lr_scheduler: cosine
72
+ max_grad_norm: 1.0
73
+ max_memory:
74
+ 0: 70GB
75
+ max_steps: 200
76
+ micro_batch_size: 1
77
+ mlflow_experiment_name: /tmp/d191cc991f4fa8fd_train_data.json
78
+ model_type: AutoModelForCausalLM
79
+ num_epochs: 2
80
+ optim_args:
81
+ adam_beta1: 0.9
82
+ adam_beta2: 0.95
83
+ adam_epsilon: 1e-5
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
+ save_steps: 50
91
+ saves_per_epoch: null
92
+ sequence_len: 1028
93
+ special_tokens:
94
+ pad_token: </s>
95
+ strict: false
96
+ tf32: false
97
+ tokenizer_type: AutoTokenizer
98
+ train_on_inputs: false
99
+ trust_remote_code: true
100
+ val_set_size: 50
101
+ wandb_entity: null
102
+ wandb_mode: online
103
+ wandb_name: 769f6c0e-9a41-483a-919d-9e4828a1a4a0
104
+ wandb_project: Gradients-On-Demand
105
+ wandb_run: your_name
106
+ wandb_runid: 769f6c0e-9a41-483a-919d-9e4828a1a4a0
107
+ warmup_steps: 10
108
+ weight_decay: 0.0
109
+ xformers_attention: null
110
+
111
+ ```
112
+
113
+ </details><br>
114
+
115
+ # 769f6c0e-9a41-483a-919d-9e4828a1a4a0
116
+
117
+ This model is a fine-tuned version of [NousResearch/CodeLlama-7b-hf-flash](https://huggingface.co/NousResearch/CodeLlama-7b-hf-flash) on the None dataset.
118
+ It achieves the following results on the evaluation set:
119
+ - Loss: 0.9611
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: 0.0003
139
+ - train_batch_size: 1
140
+ - eval_batch_size: 1
141
+ - seed: 42
142
+ - gradient_accumulation_steps: 32
143
+ - total_train_batch_size: 32
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-5
145
+ - lr_scheduler_type: cosine
146
+ - lr_scheduler_warmup_steps: 10
147
+ - training_steps: 200
148
+
149
+ ### Training results
150
+
151
+ | Training Loss | Epoch | Step | Validation Loss |
152
+ |:-------------:|:------:|:----:|:---------------:|
153
+ | 33.294 | 0.0005 | 1 | 1.2786 |
154
+ | 30.7856 | 0.0134 | 25 | 1.0777 |
155
+ | 33.5111 | 0.0268 | 50 | 1.0827 |
156
+ | 31.0323 | 0.0402 | 75 | 1.0009 |
157
+ | 32.2653 | 0.0536 | 100 | 1.0161 |
158
+ | 30.9478 | 0.0670 | 125 | 0.9712 |
159
+ | 29.0595 | 0.0804 | 150 | 0.9702 |
160
+ | 30.1167 | 0.0938 | 175 | 0.9618 |
161
+ | 21.8853 | 0.1072 | 200 | 0.9611 |
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:f6ea386fb75c489d9f80b408522b90d128155e3bf0641029818a0d27e24c934a
3
+ size 160069834