File size: 2,875 Bytes
e65d56b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: gemma
base_model: google/gemma-2-2b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-2b_hs2_accumulatesubsample_iter19_sftsd1
  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. -->

# collapse_gemma-2-2b_hs2_accumulatesubsample_iter19_sftsd1

This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2055
- Num Input Tokens Seen: 4907024

## 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: 8e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 1
- 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_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|
| No log        | 0      | 0    | 1.3909          | 0                 |
| 1.3427        | 0.0527 | 5    | 1.2782          | 258072            |
| 1.0971        | 0.1053 | 10   | 1.2131          | 521696            |
| 0.9209        | 0.1580 | 15   | 1.2167          | 782872            |
| 0.7304        | 0.2107 | 20   | 1.2697          | 1039040           |
| 0.6214        | 0.2633 | 25   | 1.2589          | 1307632           |
| 0.5449        | 0.3160 | 30   | 1.3018          | 1568000           |
| 0.521         | 0.3687 | 35   | 1.2918          | 1824608           |
| 0.4267        | 0.4213 | 40   | 1.2783          | 2087280           |
| 0.4484        | 0.4740 | 45   | 1.2457          | 2348744           |
| 0.403         | 0.5267 | 50   | 1.2346          | 2610176           |
| 0.3899        | 0.5793 | 55   | 1.2224          | 2873528           |
| 0.3705        | 0.6320 | 60   | 1.2227          | 3133328           |
| 0.3662        | 0.6847 | 65   | 1.2187          | 3395112           |
| 0.3322        | 0.7373 | 70   | 1.2076          | 3656104           |
| 0.3614        | 0.7900 | 75   | 1.2070          | 3917544           |
| 0.3462        | 0.8427 | 80   | 1.2021          | 4174120           |
| 0.3258        | 0.8953 | 85   | 1.2061          | 4437136           |
| 0.3069        | 0.9480 | 90   | 1.2061          | 4699512           |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1