File size: 2,026 Bytes
04dbefe
c0f4ee7
 
 
 
 
 
 
 
04dbefe
 
c0f4ee7
 
04dbefe
c0f4ee7
04dbefe
c0f4ee7
 
821e745
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
04dbefe
c0f4ee7
 
 
 
 
 
 
 
 
 
 
 
04dbefe
c0f4ee7
04dbefe
821e745
 
 
 
 
 
 
 
 
 
 
 
04dbefe
 
c0f4ee7
04dbefe
c0f4ee7
 
821e745
c0f4ee7
 
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
70
71
72
---
library_name: peft
license: apache-2.0
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
tags:
- generated_from_trainer
model-index:
- name: shawgpt-ft
  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. -->

# shawgpt-ft

This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1894

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2906        | 0.96  | 6    | 2.6532          |
| 2.3956        | 1.92  | 12   | 2.1305          |
| 1.9455        | 2.88  | 18   | 1.8162          |
| 1.3545        | 4.0   | 25   | 1.4919          |
| 1.3298        | 4.96  | 31   | 1.3596          |
| 1.204         | 5.92  | 37   | 1.2877          |
| 1.1487        | 6.88  | 43   | 1.2487          |
| 0.9525        | 8.0   | 50   | 1.2124          |
| 1.0795        | 8.96  | 56   | 1.1934          |
| 0.9947        | 9.6   | 60   | 1.1894          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3