update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: bert-base-uncased-finetuned-docvqa
|
| 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 |
+
# bert-base-uncased-finetuned-docvqa
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 1.9146
|
| 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: 4
|
| 38 |
+
- eval_batch_size: 4
|
| 39 |
+
- seed: 250500
|
| 40 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 41 |
+
- lr_scheduler_type: linear
|
| 42 |
+
- num_epochs: 2
|
| 43 |
+
|
| 44 |
+
### Training results
|
| 45 |
+
|
| 46 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
| 47 |
+
|:-------------:|:-----:|:-----:|:---------------:|
|
| 48 |
+
| 2.2151 | 0.1 | 1000 | 2.6299 |
|
| 49 |
+
| 1.8885 | 0.21 | 2000 | 2.2217 |
|
| 50 |
+
| 1.7353 | 0.31 | 3000 | 2.1675 |
|
| 51 |
+
| 1.6188 | 0.41 | 4000 | 2.2436 |
|
| 52 |
+
| 1.5802 | 0.52 | 5000 | 2.0539 |
|
| 53 |
+
| 1.4875 | 0.62 | 6000 | 2.0551 |
|
| 54 |
+
| 1.4675 | 0.73 | 7000 | 1.9368 |
|
| 55 |
+
| 1.3485 | 0.83 | 8000 | 1.9456 |
|
| 56 |
+
| 1.3273 | 0.93 | 9000 | 1.9281 |
|
| 57 |
+
| 1.1048 | 1.04 | 10000 | 1.9333 |
|
| 58 |
+
| 0.9529 | 1.14 | 11000 | 2.2019 |
|
| 59 |
+
| 0.9418 | 1.24 | 12000 | 2.0381 |
|
| 60 |
+
| 0.9209 | 1.35 | 13000 | 1.8753 |
|
| 61 |
+
| 0.8788 | 1.45 | 14000 | 1.9964 |
|
| 62 |
+
| 0.8729 | 1.56 | 15000 | 1.9690 |
|
| 63 |
+
| 0.8671 | 1.66 | 16000 | 1.8513 |
|
| 64 |
+
| 0.8379 | 1.76 | 17000 | 1.9627 |
|
| 65 |
+
| 0.8722 | 1.87 | 18000 | 1.8988 |
|
| 66 |
+
| 0.7842 | 1.97 | 19000 | 1.9146 |
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
### Framework versions
|
| 70 |
+
|
| 71 |
+
- Transformers 4.11.3
|
| 72 |
+
- Pytorch 1.9.0+cu111
|
| 73 |
+
- Datasets 1.14.0
|
| 74 |
+
- Tokenizers 0.10.3
|