File size: 2,916 Bytes
13f0fc2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4400a11
13f0fc2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4400a11
13f0fc2
 
 
 
 
 
4400a11
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13f0fc2
 
 
 
 
 
 
 
 
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
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3856

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4616        | 0.0   | 1    | 1.4223          |
| 1.4337        | 0.0   | 2    | 1.4204          |
| 1.6083        | 0.0   | 3    | 1.4186          |
| 1.0152        | 0.0   | 4    | 1.4168          |
| 1.5549        | 0.0   | 5    | 1.4150          |
| 1.4039        | 0.0   | 6    | 1.4132          |
| 1.0972        | 0.01  | 7    | 1.4115          |
| 1.4686        | 0.01  | 8    | 1.4098          |
| 1.3683        | 0.01  | 9    | 1.4081          |
| 1.2799        | 0.01  | 10   | 1.4065          |
| 1.2553        | 0.01  | 11   | 1.4048          |
| 1.3466        | 0.01  | 12   | 1.4032          |
| 1.1299        | 0.01  | 13   | 1.4016          |
| 1.8492        | 0.01  | 14   | 1.4000          |
| 1.3812        | 0.01  | 15   | 1.3985          |
| 1.1716        | 0.01  | 16   | 1.3970          |
| 1.1015        | 0.01  | 17   | 1.3955          |
| 1.5655        | 0.01  | 18   | 1.3942          |
| 1.4379        | 0.02  | 19   | 1.3930          |
| 1.2552        | 0.02  | 20   | 1.3918          |
| 1.1698        | 0.02  | 21   | 1.3907          |
| 1.3563        | 0.02  | 22   | 1.3897          |
| 1.6058        | 0.02  | 23   | 1.3889          |
| 1.4902        | 0.02  | 24   | 1.3881          |
| 1.6846        | 0.02  | 25   | 1.3874          |
| 1.2315        | 0.02  | 26   | 1.3868          |
| 1.0901        | 0.02  | 27   | 1.3863          |
| 1.2795        | 0.02  | 28   | 1.3860          |
| 1.1802        | 0.02  | 29   | 1.3857          |
| 1.2028        | 0.02  | 30   | 1.3856          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2