YaraKyrychenko
commited on
Commit
•
55e15b7
1
Parent(s):
1375af7
update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,69 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
metrics:
|
6 |
+
- accuracy
|
7 |
+
- f1
|
8 |
+
- precision
|
9 |
+
- recall
|
10 |
+
model-index:
|
11 |
+
- name: xlm-roberta-base-ukraine-war-official
|
12 |
+
results: []
|
13 |
+
---
|
14 |
+
|
15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
16 |
+
should probably proofread and complete it, then remove this comment. -->
|
17 |
+
|
18 |
+
# xlm-roberta-base-ukraine-war-official
|
19 |
+
|
20 |
+
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
|
21 |
+
It achieves the following results on the evaluation set:
|
22 |
+
- Loss: 0.5147
|
23 |
+
- Accuracy: 0.776
|
24 |
+
- F1: 0.7747
|
25 |
+
- Precision: 0.7824
|
26 |
+
- Recall: 0.776
|
27 |
+
|
28 |
+
## Model description
|
29 |
+
|
30 |
+
More information needed
|
31 |
+
|
32 |
+
## Intended uses & limitations
|
33 |
+
|
34 |
+
More information needed
|
35 |
+
|
36 |
+
## Training and evaluation data
|
37 |
+
|
38 |
+
More information needed
|
39 |
+
|
40 |
+
## Training procedure
|
41 |
+
|
42 |
+
### Training hyperparameters
|
43 |
+
|
44 |
+
The following hyperparameters were used during training:
|
45 |
+
- learning_rate: 5e-05
|
46 |
+
- train_batch_size: 16
|
47 |
+
- eval_batch_size: 64
|
48 |
+
- seed: 123
|
49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
50 |
+
- lr_scheduler_type: linear
|
51 |
+
- lr_scheduler_warmup_steps: 500
|
52 |
+
- num_epochs: 5
|
53 |
+
|
54 |
+
### Training results
|
55 |
+
|
56 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|
57 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
|
58 |
+
| 0.4394 | 1.0 | 1875 | 0.3915 | 0.8365 | 0.8362 | 0.8386 | 0.8365 |
|
59 |
+
| 0.4008 | 2.0 | 3750 | 0.3924 | 0.8325 | 0.8309 | 0.8459 | 0.8325 |
|
60 |
+
| 0.3456 | 3.0 | 5625 | 0.3699 | 0.8525 | 0.8524 | 0.8533 | 0.8525 |
|
61 |
+
| 0.298 | 4.0 | 7500 | 0.3894 | 0.8485 | 0.8479 | 0.8540 | 0.8485 |
|
62 |
+
| 0.2531 | 5.0 | 9375 | 0.4359 | 0.8475 | 0.8469 | 0.8528 | 0.8475 |
|
63 |
+
|
64 |
+
|
65 |
+
### Framework versions
|
66 |
+
|
67 |
+
- Transformers 4.28.0
|
68 |
+
- Pytorch 2.0.0+cu118
|
69 |
+
- Tokenizers 0.13.3
|