File size: 1,218 Bytes
bc1765b
9a30b90
 
 
 
 
 
 
 
 
 
bc1765b
 
9a30b90
 
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
bc1765b
9a30b90
 
 
 
 
 
 
 
 
 
 
bc1765b
9a30b90
bc1765b
 
 
9a30b90
bc1765b
9a30b90
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
---
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b-it
model-index:
- name: ft-google-gemma-2b-it-qlora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ft-google-gemma-2b-it-qlora

This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on the None dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2