File size: 1,693 Bytes
f6ef825
 
 
 
 
 
 
63dab02
 
f6ef825
 
 
 
 
 
 
 
 
 
63dab02
f6ef825
20adfa6
f6ef825
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
91efe70
20adfa6
 
f6ef825
 
 
20adfa6
f6ef825
63dab02
91efe70
20adfa6
f6ef825
 
 
7b1f212
 
20adfa6
 
 
 
f6ef825
 
 
 
 
 
 
 
 
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
60
61
62
63
64
65
66
67
68
69
---
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: ytcheng/llama-3-8b-hf-sm-lora-merged
datasets:
- generator
model-index:
- name: llama-3-8b-hf-ft-chat-lora
  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. -->

# llama-3-8b-hf-ft-chat-lora

This model is a fine-tuned version of [ytcheng/llama-3-8b-hf-sm-lora-merged](https://huggingface.co/ytcheng/llama-3-8b-hf-sm-lora-merged) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8363

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.3345        | 0.9963 | 133  | 2.4116          |
| 1.9916        | 2.0    | 267  | 3.9850          |
| 1.8552        | 2.9963 | 400  | 4.8651          |
| 1.8627        | 3.9850 | 532  | 4.8363          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1