update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: distilroberta-propaganda-2class
|
| 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 |
+
# distilroberta-propaganda-2class
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 0.5087
|
| 18 |
+
- Acc: 0.7424
|
| 19 |
+
|
| 20 |
+
## Model description
|
| 21 |
+
|
| 22 |
+
More information needed
|
| 23 |
+
|
| 24 |
+
## Intended uses & limitations
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Training and evaluation data
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training procedure
|
| 33 |
+
|
| 34 |
+
### Training hyperparameters
|
| 35 |
+
|
| 36 |
+
The following hyperparameters were used during training:
|
| 37 |
+
- learning_rate: 5e-05
|
| 38 |
+
- train_batch_size: 32
|
| 39 |
+
- eval_batch_size: 32
|
| 40 |
+
- seed: 12345
|
| 41 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 42 |
+
- lr_scheduler_type: linear
|
| 43 |
+
- lr_scheduler_warmup_steps: 16
|
| 44 |
+
- num_epochs: 20
|
| 45 |
+
- mixed_precision_training: Native AMP
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | Acc |
|
| 50 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|
|
| 51 |
+
| 0.5737 | 1.0 | 493 | 0.5998 | 0.6515 |
|
| 52 |
+
| 0.4954 | 2.0 | 986 | 0.5530 | 0.7080 |
|
| 53 |
+
| 0.4774 | 3.0 | 1479 | 0.5331 | 0.7258 |
|
| 54 |
+
| 0.4846 | 4.0 | 1972 | 0.5247 | 0.7339 |
|
| 55 |
+
| 0.4749 | 5.0 | 2465 | 0.5392 | 0.7199 |
|
| 56 |
+
| 0.502 | 6.0 | 2958 | 0.5124 | 0.7466 |
|
| 57 |
+
| 0.457 | 7.0 | 3451 | 0.5167 | 0.7432 |
|
| 58 |
+
| 0.4899 | 8.0 | 3944 | 0.5160 | 0.7428 |
|
| 59 |
+
| 0.4833 | 9.0 | 4437 | 0.5280 | 0.7339 |
|
| 60 |
+
| 0.5114 | 10.0 | 4930 | 0.5112 | 0.7436 |
|
| 61 |
+
| 0.4419 | 11.0 | 5423 | 0.5060 | 0.7525 |
|
| 62 |
+
| 0.4743 | 12.0 | 5916 | 0.5031 | 0.7547 |
|
| 63 |
+
| 0.4597 | 13.0 | 6409 | 0.5043 | 0.7517 |
|
| 64 |
+
| 0.4861 | 14.0 | 6902 | 0.5055 | 0.7487 |
|
| 65 |
+
| 0.499 | 15.0 | 7395 | 0.5091 | 0.7419 |
|
| 66 |
+
| 0.501 | 16.0 | 7888 | 0.5037 | 0.7521 |
|
| 67 |
+
| 0.4659 | 17.0 | 8381 | 0.5087 | 0.7424 |
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
### Framework versions
|
| 71 |
+
|
| 72 |
+
- Transformers 4.11.2
|
| 73 |
+
- Pytorch 1.7.1
|
| 74 |
+
- Datasets 1.11.0
|
| 75 |
+
- Tokenizers 0.10.3
|