khanhdhq commited on
Commit
6f68743
1 Parent(s): b1557e8

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +47 -13
README.md CHANGED
@@ -1,20 +1,54 @@
1
  ---
2
- library_name: peft
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4
  ## Training procedure
5
 
 
6
 
7
- The following `bitsandbytes` quantization config was used during training:
8
- - load_in_8bit: False
9
- - load_in_4bit: True
10
- - llm_int8_threshold: 6.0
11
- - llm_int8_skip_modules: None
12
- - llm_int8_enable_fp32_cpu_offload: False
13
- - llm_int8_has_fp16_weight: False
14
- - bnb_4bit_quant_type: nf4
15
- - bnb_4bit_use_double_quant: True
16
- - bnb_4bit_compute_dtype: bfloat16
17
- ### Framework versions
 
 
18
 
19
 
20
- - PEFT 0.4.0.dev0
 
 
 
 
 
 
 
1
  ---
2
+ license: other
3
+ tags:
4
+ - generated_from_trainer
5
+ model-index:
6
+ - name: test_vietcuna_ep1_lr0.0002
7
+ results: []
8
  ---
9
+
10
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
+ should probably proofread and complete it, then remove this comment. -->
12
+
13
+ # test_vietcuna_ep1_lr0.0002
14
+
15
+ This model is a fine-tuned version of [vilm/vietcuna-3b](https://huggingface.co/vilm/vietcuna-3b) on an unknown dataset.
16
+
17
+ ## Model description
18
+
19
+ More information needed
20
+
21
+ ## Intended uses & limitations
22
+
23
+ More information needed
24
+
25
+ ## Training and evaluation data
26
+
27
+ More information needed
28
+
29
  ## Training procedure
30
 
31
+ ### Training hyperparameters
32
 
33
+ The following hyperparameters were used during training:
34
+ - learning_rate: 0.0002
35
+ - train_batch_size: 4
36
+ - eval_batch_size: 8
37
+ - seed: 42
38
+ - gradient_accumulation_steps: 4
39
+ - total_train_batch_size: 16
40
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
+ - lr_scheduler_type: linear
42
+ - lr_scheduler_warmup_steps: 2
43
+ - num_epochs: 1
44
+
45
+ ### Training results
46
 
47
 
48
+
49
+ ### Framework versions
50
+
51
+ - Transformers 4.31.0.dev0
52
+ - Pytorch 2.0.1+cu118
53
+ - Datasets 2.13.0
54
+ - Tokenizers 0.13.3