update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: cc-by-nc-sa-4.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
model-index:
|
6 |
+
- name: layoutlmv2-large-uncased-finetuned-vi-infovqa
|
7 |
+
results: []
|
8 |
+
---
|
9 |
+
|
10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
11 |
+
should probably proofread and complete it, then remove this comment. -->
|
12 |
+
|
13 |
+
# layoutlmv2-large-uncased-finetuned-vi-infovqa
|
14 |
+
|
15 |
+
This model is a fine-tuned version of [microsoft/layoutlmv2-large-uncased](https://huggingface.co/microsoft/layoutlmv2-large-uncased) on an unknown dataset.
|
16 |
+
It achieves the following results on the evaluation set:
|
17 |
+
- Loss: 6.2383
|
18 |
+
|
19 |
+
## Model description
|
20 |
+
|
21 |
+
More information needed
|
22 |
+
|
23 |
+
## Intended uses & limitations
|
24 |
+
|
25 |
+
More information needed
|
26 |
+
|
27 |
+
## Training and evaluation data
|
28 |
+
|
29 |
+
More information needed
|
30 |
+
|
31 |
+
## Training procedure
|
32 |
+
|
33 |
+
### Training hyperparameters
|
34 |
+
|
35 |
+
The following hyperparameters were used during training:
|
36 |
+
- learning_rate: 5e-05
|
37 |
+
- train_batch_size: 2
|
38 |
+
- eval_batch_size: 2
|
39 |
+
- seed: 250500
|
40 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
41 |
+
- lr_scheduler_type: linear
|
42 |
+
- num_epochs: 10
|
43 |
+
|
44 |
+
### Training results
|
45 |
+
|
46 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
47 |
+
|:-------------:|:-----:|:----:|:---------------:|
|
48 |
+
| 5.9983 | 0.83 | 500 | 6.2383 |
|
49 |
+
| 6.2621 | 1.65 | 1000 | 6.2383 |
|
50 |
+
| 6.2492 | 2.48 | 1500 | 6.2383 |
|
51 |
+
| 6.2548 | 3.3 | 2000 | 6.2383 |
|
52 |
+
| 6.2515 | 4.13 | 2500 | 6.2383 |
|
53 |
+
| 6.2543 | 4.95 | 3000 | 6.2383 |
|
54 |
+
| 6.2545 | 5.78 | 3500 | 6.2383 |
|
55 |
+
| 6.247 | 6.6 | 4000 | 6.2383 |
|
56 |
+
| 6.2499 | 7.43 | 4500 | 6.2383 |
|
57 |
+
| 6.2434 | 8.25 | 5000 | 6.2383 |
|
58 |
+
| 6.2416 | 9.08 | 5500 | 6.2383 |
|
59 |
+
| 6.2425 | 9.9 | 6000 | 6.2383 |
|
60 |
+
|
61 |
+
|
62 |
+
### Framework versions
|
63 |
+
|
64 |
+
- Transformers 4.14.1
|
65 |
+
- Pytorch 1.8.0+cu101
|
66 |
+
- Datasets 1.16.1
|
67 |
+
- Tokenizers 0.10.3
|