File size: 1,954 Bytes
ea8f50d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-floors
  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-floors

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0322
- Wer Score: 1.8463

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 6.8447        | 4.76  | 50   | 4.1895          | 2.2204    |
| 2.1937        | 9.52  | 100  | 0.4359          | 3.1889    |
| 0.1385        | 14.29 | 150  | 0.0360          | 0.1426    |
| 0.0184        | 19.05 | 200  | 0.0307          | 0.6185    |
| 0.0117        | 23.81 | 250  | 0.0287          | 0.1741    |
| 0.0095        | 28.57 | 300  | 0.0293          | 1.1463    |
| 0.0081        | 33.33 | 350  | 0.0292          | 0.8463    |
| 0.0061        | 38.1  | 400  | 0.0312          | 2.0333    |
| 0.0044        | 42.86 | 450  | 0.0322          | 1.9204    |
| 0.0032        | 47.62 | 500  | 0.0322          | 1.8463    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2