update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,76 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- mn
|
| 4 |
+
license: mit
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
metrics:
|
| 8 |
+
- precision
|
| 9 |
+
- recall
|
| 10 |
+
- f1
|
| 11 |
+
- accuracy
|
| 12 |
+
model-index:
|
| 13 |
+
- name: xlm-roberta-base-mongolian-ner
|
| 14 |
+
results: []
|
| 15 |
+
---
|
| 16 |
+
|
| 17 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 18 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 19 |
+
|
| 20 |
+
# xlm-roberta-base-mongolian-ner
|
| 21 |
+
|
| 22 |
+
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
|
| 23 |
+
It achieves the following results on the evaluation set:
|
| 24 |
+
- Loss: 0.1166
|
| 25 |
+
- Precision: 0.9251
|
| 26 |
+
- Recall: 0.9335
|
| 27 |
+
- F1: 0.9293
|
| 28 |
+
- Accuracy: 0.9787
|
| 29 |
+
|
| 30 |
+
## Model description
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Intended uses & limitations
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training and evaluation data
|
| 39 |
+
|
| 40 |
+
More information needed
|
| 41 |
+
|
| 42 |
+
## Training procedure
|
| 43 |
+
|
| 44 |
+
### Training hyperparameters
|
| 45 |
+
|
| 46 |
+
The following hyperparameters were used during training:
|
| 47 |
+
- learning_rate: 2e-05
|
| 48 |
+
- train_batch_size: 16
|
| 49 |
+
- eval_batch_size: 32
|
| 50 |
+
- seed: 42
|
| 51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 52 |
+
- lr_scheduler_type: linear
|
| 53 |
+
- num_epochs: 10
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 59 |
+
| 0.2013 | 1.0 | 477 | 0.0958 | 0.8951 | 0.9124 | 0.9037 | 0.9731 |
|
| 60 |
+
| 0.0846 | 2.0 | 954 | 0.0825 | 0.9155 | 0.9240 | 0.9197 | 0.9774 |
|
| 61 |
+
| 0.0622 | 3.0 | 1431 | 0.0844 | 0.9109 | 0.9235 | 0.9172 | 0.9766 |
|
| 62 |
+
| 0.0456 | 4.0 | 1908 | 0.0940 | 0.9174 | 0.9266 | 0.9220 | 0.9767 |
|
| 63 |
+
| 0.0347 | 5.0 | 2385 | 0.1015 | 0.9184 | 0.9284 | 0.9234 | 0.9770 |
|
| 64 |
+
| 0.0253 | 6.0 | 2862 | 0.1117 | 0.9174 | 0.9254 | 0.9214 | 0.9764 |
|
| 65 |
+
| 0.0203 | 7.0 | 3339 | 0.1147 | 0.9225 | 0.9310 | 0.9267 | 0.9780 |
|
| 66 |
+
| 0.0152 | 8.0 | 3816 | 0.1129 | 0.9229 | 0.9316 | 0.9272 | 0.9779 |
|
| 67 |
+
| 0.0129 | 9.0 | 4293 | 0.1150 | 0.9245 | 0.9324 | 0.9285 | 0.9784 |
|
| 68 |
+
| 0.0102 | 10.0 | 4770 | 0.1166 | 0.9251 | 0.9335 | 0.9293 | 0.9787 |
|
| 69 |
+
|
| 70 |
+
|
| 71 |
+
### Framework versions
|
| 72 |
+
|
| 73 |
+
- Transformers 4.28.0
|
| 74 |
+
- Pytorch 2.0.1+cu118
|
| 75 |
+
- Datasets 2.12.0
|
| 76 |
+
- Tokenizers 0.13.3
|