sahanes commited on
Commit
0011df3
1 Parent(s): bffc6d9

End of training

Browse files
Files changed (1) hide show
  1. README.md +164 -3
README.md CHANGED
@@ -1,3 +1,164 @@
1
- ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ library_name: peft
4
+ tags:
5
+ - axolotl
6
+ - generated_from_trainer
7
+ base_model: mistralai/Mistral-7B-v0.1
8
+ model-index:
9
+ - name: finetuning-mistral-alpaca
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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
17
+ <details><summary>See axolotl config</summary>
18
+
19
+ axolotl version: `0.4.0`
20
+ ```yaml
21
+ base_model: mistralai/Mistral-7B-v0.1
22
+ model_type: MistralForCausalLM
23
+ tokenizer_type: LlamaTokenizer
24
+ is_mistral_derived_model: true
25
+
26
+ load_in_8bit: false
27
+ load_in_4bit: true
28
+ strict: false
29
+
30
+ lora_fan_in_fan_out: false
31
+ data_seed: 49
32
+ seed: 49
33
+
34
+ datasets:
35
+ - path: sample_data/alpaca_synth_queries.jsonl
36
+ type: sharegpt
37
+ conversation: alpaca
38
+ dataset_prepared_path: last_run_prepared
39
+ val_set_size: 0.1
40
+ output_dir: ./qlora-alpaca-out
41
+ #hub_model_id: hamel/hc-mistral-alpaca
42
+ hub_model_id: sahanes/finetuning-mistral-alpaca
43
+ adapter: qlora
44
+ lora_model_dir:
45
+
46
+ sequence_len: 896
47
+ sample_packing: false
48
+ pad_to_sequence_len: true
49
+
50
+ lora_r: 32
51
+ lora_alpha: 16
52
+ lora_dropout: 0.05
53
+ lora_target_linear: true
54
+ lora_fan_in_fan_out:
55
+ lora_target_modules:
56
+ - gate_proj
57
+ - down_proj
58
+ - up_proj
59
+ - q_proj
60
+ - v_proj
61
+ - k_proj
62
+ - o_proj
63
+
64
+ #wandb_project: hc-axolotl-mistral
65
+ #wandb_entity: hamelsmu
66
+
67
+ gradient_accumulation_steps: 4
68
+ micro_batch_size: 16
69
+ eval_batch_size: 16
70
+ num_epochs: 3
71
+ optimizer: adamw_bnb_8bit
72
+ lr_scheduler: cosine
73
+ learning_rate: 0.0002
74
+ max_grad_norm: 1.0
75
+ adam_beta2: 0.95
76
+ adam_epsilon: 0.00001
77
+ save_total_limit: 12
78
+
79
+ train_on_inputs: false
80
+ group_by_length: false
81
+ bf16: true
82
+ fp16: false
83
+ tf32: false
84
+
85
+ gradient_checkpointing: true
86
+ early_stopping_patience:
87
+ resume_from_checkpoint:
88
+ local_rank:
89
+ logging_steps: 1
90
+ xformers_attention:
91
+ flash_attention: true
92
+
93
+ loss_watchdog_threshold: 5.0
94
+ loss_watchdog_patience: 3
95
+
96
+ warmup_steps: 20
97
+ evals_per_epoch: 4
98
+ eval_table_size:
99
+ eval_table_max_new_tokens: 128
100
+ saves_per_epoch: 6
101
+ debug:
102
+ weight_decay: 0.0
103
+ fsdp:
104
+ fsdp_config:
105
+ special_tokens:
106
+ bos_token: "<s>"
107
+ eos_token: "</s>"
108
+ unk_token: "<unk>"
109
+ save_safetensors: true
110
+
111
+ ```
112
+
113
+ </details><br>
114
+
115
+ # finetuning-mistral-alpaca
116
+
117
+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
118
+ It achieves the following results on the evaluation set:
119
+ - Loss: 1.2479
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: 0.0002
139
+ - train_batch_size: 16
140
+ - eval_batch_size: 16
141
+ - seed: 49
142
+ - gradient_accumulation_steps: 4
143
+ - total_train_batch_size: 64
144
+ - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
145
+ - lr_scheduler_type: cosine
146
+ - lr_scheduler_warmup_steps: 20
147
+ - num_epochs: 3
148
+
149
+ ### Training results
150
+
151
+ | Training Loss | Epoch | Step | Validation Loss |
152
+ |:-------------:|:------:|:----:|:---------------:|
153
+ | 1.334 | 0.6667 | 1 | 1.2849 |
154
+ | 1.3476 | 1.3333 | 2 | 1.2759 |
155
+ | 1.2982 | 2.0 | 3 | 1.2479 |
156
+
157
+
158
+ ### Framework versions
159
+
160
+ - PEFT 0.10.0
161
+ - Transformers 4.40.2
162
+ - Pytorch 2.1.2+cu118
163
+ - Datasets 2.19.1
164
+ - Tokenizers 0.19.1