File size: 2,692 Bytes
ab3da25
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: git-base-one-5e-5-25
  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. -->

# git-base-one-5e-5-25

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8238
- Wer Score: 5.8

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| No log        | 1.25  | 5    | 9.5084          | 50.1      |
| 9.9196        | 2.5   | 10   | 8.4842          | 64.85     |
| 9.9196        | 3.75  | 15   | 7.9215          | 67.6      |
| 8.0697        | 5.0   | 20   | 7.4826          | 66.45     |
| 8.0697        | 6.25  | 25   | 7.0776          | 53.95     |
| 7.2067        | 7.5   | 30   | 6.6926          | 18.05     |
| 7.2067        | 8.75  | 35   | 6.3268          | 17.6      |
| 6.4594        | 10.0  | 40   | 5.9807          | 19.8      |
| 6.4594        | 11.25 | 45   | 5.6568          | 19.35     |
| 5.7908        | 12.5  | 50   | 5.3563          | 6.15      |
| 5.7908        | 13.75 | 55   | 5.0803          | 6.2       |
| 5.2135        | 15.0  | 60   | 4.8305          | 5.8       |
| 5.2135        | 16.25 | 65   | 4.6068          | 5.75      |
| 4.7358        | 17.5  | 70   | 4.4111          | 5.8       |
| 4.7358        | 18.75 | 75   | 4.2427          | 5.8       |
| 4.3652        | 20.0  | 80   | 4.1027          | 5.8       |
| 4.3652        | 21.25 | 85   | 3.9908          | 5.8       |
| 4.1076        | 22.5  | 90   | 3.9070          | 5.8       |
| 4.1076        | 23.75 | 95   | 3.8515          | 5.8       |
| 3.9616        | 25.0  | 100  | 3.8238          | 5.8       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1