Commit
•
f5ae8b2
1
Parent(s):
1105cc7
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,80 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: contract-ner-model-da
|
| 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 |
+
# contract-ner-model-da
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 0.0100
|
| 18 |
+
- Micro F1: 0.9074
|
| 19 |
+
- Micro F1 No Misc: 0.9074
|
| 20 |
+
|
| 21 |
+
## Model description
|
| 22 |
+
|
| 23 |
+
More information needed
|
| 24 |
+
|
| 25 |
+
## Intended uses & limitations
|
| 26 |
+
|
| 27 |
+
More information needed
|
| 28 |
+
|
| 29 |
+
## Training and evaluation data
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Training procedure
|
| 34 |
+
|
| 35 |
+
### Training hyperparameters
|
| 36 |
+
|
| 37 |
+
The following hyperparameters were used during training:
|
| 38 |
+
- learning_rate: 2e-05
|
| 39 |
+
- train_batch_size: 8
|
| 40 |
+
- eval_batch_size: 8
|
| 41 |
+
- seed: 42
|
| 42 |
+
- gradient_accumulation_steps: 4
|
| 43 |
+
- total_train_batch_size: 32
|
| 44 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 45 |
+
- lr_scheduler_type: linear
|
| 46 |
+
- lr_scheduler_warmup_steps: 4356
|
| 47 |
+
- num_epochs: 100
|
| 48 |
+
|
| 49 |
+
### Training results
|
| 50 |
+
|
| 51 |
+
| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Micro F1 No Misc |
|
| 52 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|
|
| 53 |
+
| 1.1722 | 4.88 | 200 | 0.0612 | 0.0 | 0.0 |
|
| 54 |
+
| 0.0341 | 9.76 | 400 | 0.0209 | 0.0 | 0.0 |
|
| 55 |
+
| 0.0158 | 14.63 | 600 | 0.0109 | 0.7233 | 0.7233 |
|
| 56 |
+
| 0.0085 | 19.51 | 800 | 0.0097 | 0.7727 | 0.7727 |
|
| 57 |
+
| 0.0057 | 24.39 | 1000 | 0.0084 | 0.8319 | 0.8319 |
|
| 58 |
+
| 0.0041 | 29.27 | 1200 | 0.0085 | 0.8630 | 0.8630 |
|
| 59 |
+
| 0.0031 | 34.15 | 1400 | 0.0089 | 0.8261 | 0.8261 |
|
| 60 |
+
| 0.0023 | 39.02 | 1600 | 0.0066 | 0.8785 | 0.8785 |
|
| 61 |
+
| 0.0017 | 43.9 | 1800 | 0.0106 | 0.8164 | 0.8164 |
|
| 62 |
+
| 0.0012 | 48.78 | 2000 | 0.0092 | 0.8730 | 0.8730 |
|
| 63 |
+
| 0.0008 | 53.66 | 2200 | 0.0076 | 0.8868 | 0.8868 |
|
| 64 |
+
| 0.0007 | 58.54 | 2400 | 0.0075 | 0.9017 | 0.9017 |
|
| 65 |
+
| 0.0005 | 63.41 | 2600 | 0.0096 | 0.8806 | 0.8806 |
|
| 66 |
+
| 0.0004 | 68.29 | 2800 | 0.0094 | 0.8852 | 0.8852 |
|
| 67 |
+
| 0.0004 | 73.17 | 3000 | 0.0084 | 0.9126 | 0.9126 |
|
| 68 |
+
| 0.0003 | 78.05 | 3200 | 0.0083 | 0.8986 | 0.8986 |
|
| 69 |
+
| 0.0003 | 82.93 | 3400 | 0.0093 | 0.9144 | 0.9144 |
|
| 70 |
+
| 0.0003 | 87.8 | 3600 | 0.0088 | 0.9231 | 0.9231 |
|
| 71 |
+
| 0.0001 | 92.68 | 3800 | 0.0080 | 0.9280 | 0.9280 |
|
| 72 |
+
| 0.0002 | 97.56 | 4000 | 0.0100 | 0.9074 | 0.9074 |
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
### Framework versions
|
| 76 |
+
|
| 77 |
+
- Transformers 4.11.3
|
| 78 |
+
- Pytorch 1.9.0+cu111
|
| 79 |
+
- Datasets 1.14.0
|
| 80 |
+
- Tokenizers 0.10.3
|