fats-fme commited on
Commit
83b85bf
1 Parent(s): 9be8e7a

End of training

Browse files
Files changed (2) hide show
  1. README.md +166 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,166 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: apache-2.0
4
+ base_model: teknium/OpenHermes-2.5-Mistral-7B
5
+ tags:
6
+ - axolotl
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: b0ffab7b-58fa-475f-950e-ba65c623bb7f
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: teknium/OpenHermes-2.5-Mistral-7B
23
+ bf16: true
24
+ chat_template: llama3
25
+ dataset_prepared_path: null
26
+ datasets:
27
+ - data_files:
28
+ - 5249a1b83c51e8f1_train_data.json
29
+ ds_type: json
30
+ format: custom
31
+ path: /workspace/input_data/5249a1b83c51e8f1_train_data.json
32
+ type:
33
+ field_input: input
34
+ field_instruction: instruction
35
+ field_output: response
36
+ format: '{instruction} {input}'
37
+ no_input_format: '{instruction}'
38
+ system_format: '{system}'
39
+ system_prompt: ''
40
+ ddp_find_unused_parameters: false
41
+ distributed_type: ddp
42
+ early_stopping_patience: null
43
+ env:
44
+ CUDA_VISIBLE_DEVICES: 0,1
45
+ MASTER_ADDR: localhost
46
+ MASTER_PORT: '29500'
47
+ NCCL_DEBUG: INFO
48
+ NCCL_IB_DISABLE: '0'
49
+ NCCL_P2P_DISABLE: '0'
50
+ NCCL_P2P_LEVEL: NVL
51
+ PYTORCH_CUDA_ALLOC_CONF: max_split_size_mb:512, garbage_collection_threshold:0.8
52
+ WORLD_SIZE: '2'
53
+ eval_max_new_tokens: 128
54
+ eval_table_size: null
55
+ evals_per_epoch: 4
56
+ flash_attention: true
57
+ fp16: false
58
+ gradient_accumulation_steps: 8
59
+ gradient_checkpointing: false
60
+ group_by_length: true
61
+ hub_model_id: fats-fme/b0ffab7b-58fa-475f-950e-ba65c623bb7f
62
+ hub_repo: null
63
+ hub_strategy: checkpoint
64
+ hub_token: null
65
+ learning_rate: 0.0002
66
+ load_in_4bit: false
67
+ load_in_8bit: false
68
+ logging_steps: 1
69
+ lora_alpha: 32
70
+ lora_dropout: 0.05
71
+ lora_fan_in_fan_out: null
72
+ lora_model_dir: null
73
+ lora_r: 16
74
+ lora_target_linear: true
75
+ lr_scheduler: cosine
76
+ max_memory_MB: 65000
77
+ max_steps: -1
78
+ micro_batch_size: 2
79
+ mlflow_experiment_name: /tmp/5249a1b83c51e8f1_train_data.json
80
+ model_type: AutoModelForCausalLM
81
+ num_devices: 2
82
+ num_epochs: 1
83
+ optimizer: adamw_torch
84
+ output_dir: miner_id_24
85
+ pad_to_sequence_len: true
86
+ resume_from_checkpoint: null
87
+ s2_attention: null
88
+ sample_packing: false
89
+ saves_per_epoch: 4
90
+ sequence_len: 4056
91
+ special_tokens:
92
+ pad_token: <|im_end|>
93
+ strict: false
94
+ tf32: true
95
+ tokenizer_type: AutoTokenizer
96
+ train_on_inputs: false
97
+ trust_remote_code: true
98
+ val_set_size: 0.05
99
+ wandb_entity: null
100
+ wandb_mode: online
101
+ wandb_name: b0ffab7b-58fa-475f-950e-ba65c623bb7f
102
+ wandb_project: Gradients-On-Demand
103
+ wandb_run: your_name
104
+ wandb_runid: b0ffab7b-58fa-475f-950e-ba65c623bb7f
105
+ warmup_steps: 20
106
+ world_size: 2
107
+ xformers_attention: true
108
+
109
+ ```
110
+
111
+ </details><br>
112
+
113
+ # b0ffab7b-58fa-475f-950e-ba65c623bb7f
114
+
115
+ This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset.
116
+ It achieves the following results on the evaluation set:
117
+ - Loss: 0.1233
118
+
119
+ ## Model description
120
+
121
+ More information needed
122
+
123
+ ## Intended uses & limitations
124
+
125
+ More information needed
126
+
127
+ ## Training and evaluation data
128
+
129
+ More information needed
130
+
131
+ ## Training procedure
132
+
133
+ ### Training hyperparameters
134
+
135
+ The following hyperparameters were used during training:
136
+ - learning_rate: 0.0002
137
+ - train_batch_size: 2
138
+ - eval_batch_size: 2
139
+ - seed: 42
140
+ - distributed_type: multi-GPU
141
+ - num_devices: 2
142
+ - gradient_accumulation_steps: 8
143
+ - total_train_batch_size: 32
144
+ - total_eval_batch_size: 4
145
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
146
+ - lr_scheduler_type: cosine
147
+ - lr_scheduler_warmup_steps: 20
148
+ - num_epochs: 1
149
+
150
+ ### Training results
151
+
152
+ | Training Loss | Epoch | Step | Validation Loss |
153
+ |:-------------:|:------:|:----:|:---------------:|
154
+ | 5.8683 | 0.0004 | 1 | 0.8921 |
155
+ | 4.6862 | 0.2503 | 661 | 0.4859 |
156
+ | 1.5248 | 0.5006 | 1322 | 0.2775 |
157
+ | 1.0347 | 0.7509 | 1983 | 0.1233 |
158
+
159
+
160
+ ### Framework versions
161
+
162
+ - PEFT 0.13.2
163
+ - Transformers 4.46.0
164
+ - Pytorch 2.5.0+cu124
165
+ - Datasets 3.0.1
166
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:483e415b5440167357cab287d6af0211f57b8f92b93a1a3b14cc0028fbe6f966
3
+ size 167934026