File size: 2,493 Bytes
cf36f0b
 
c96a7fd
 
 
 
cf36f0b
 
 
c96a7fd
cf36f0b
 
 
 
 
 
 
 
 
 
 
 
 
c96a7fd
cf36f0b
c96a7fd
cf36f0b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
- GaetanMichelet/chat-120_ft_task-1_auto
- GaetanMichelet/chat-180_ft_task-1_auto
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-1_180-samples_config-2_full_auto
  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. -->

# Gemma-2-2B_task-1_180-samples_config-2_full_auto

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the GaetanMichelet/chat-60_ft_task-1_auto, the GaetanMichelet/chat-120_ft_task-1_auto and the GaetanMichelet/chat-180_ft_task-1_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9375

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- 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: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.2783        | 0.9412  | 8    | 2.2320          |
| 1.8925        | 2.0     | 17   | 1.7374          |
| 1.479         | 2.9412  | 25   | 1.3322          |
| 1.0469        | 4.0     | 34   | 1.0631          |
| 0.962         | 4.9412  | 42   | 0.9939          |
| 0.9343        | 6.0     | 51   | 0.9545          |
| 0.8325        | 6.9412  | 59   | 0.9375          |
| 0.7698        | 8.0     | 68   | 0.9379          |
| 0.6897        | 8.9412  | 76   | 0.9577          |
| 0.5925        | 10.0    | 85   | 1.0182          |
| 0.506         | 10.9412 | 93   | 1.1055          |
| 0.3319        | 12.0    | 102  | 1.2682          |
| 0.2649        | 12.9412 | 110  | 1.4429          |
| 0.2121        | 14.0    | 119  | 1.6486          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1