vlkn commited on
Commit
4716dfa
1 Parent(s): 157cd3e

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +42 -13
README.md CHANGED
@@ -1,20 +1,49 @@
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: False
16
- - bnb_4bit_compute_dtype: float16
17
- ### Framework versions
18
 
 
19
 
20
- - PEFT 0.4.0.dev0
 
 
 
 
1
  ---
2
+ tags:
3
+ - generated_from_trainer
4
+ model-index:
5
+ - name: falcon_finetuned
6
+ results: []
7
  ---
8
+
9
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
10
+ should probably proofread and complete it, then remove this comment. -->
11
+
12
+ # falcon_finetuned
13
+
14
+ This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharded-bf16) on an unknown dataset.
15
+
16
+ ## Model description
17
+
18
+ More information needed
19
+
20
+ ## Intended uses & limitations
21
+
22
+ More information needed
23
+
24
+ ## Training and evaluation data
25
+
26
+ More information needed
27
+
28
  ## Training procedure
29
 
30
+ ### Training hyperparameters
31
 
32
+ The following hyperparameters were used during training:
33
+ - learning_rate: 0.0002
34
+ - train_batch_size: 4
35
+ - eval_batch_size: 8
36
+ - seed: 42
37
+ - gradient_accumulation_steps: 4
38
+ - total_train_batch_size: 16
39
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
40
+ - lr_scheduler_type: constant
41
+ - lr_scheduler_warmup_ratio: 0.03
42
+ - training_steps: 500
43
 
44
+ ### Framework versions
45
 
46
+ - Transformers 4.30.2
47
+ - Pytorch 2.0.1+cu118
48
+ - Datasets 2.13.1
49
+ - Tokenizers 0.13.3