File size: 2,419 Bytes
6b4a112 6b984b3 6b4a112 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: stance_class_l
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# stance_class_l
This model is a fine-tuned version of vinai/bertweet-base on the dataset of 804 labeled tweets on the cancer risk controversy of Roundup Weedkiller \.
It classified the stance of an individual's tweet toward Bayer, Monsanto, or other relevant organizations in the crisis.
Two stances are classified: (0) Aggressive, (1) Non-Aggressive (neutral and accommodative).
It achieves the following results on the evaluation set:
- Loss: 0.6084
- Accuracy: 0.8447
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2.924e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3566 | 1.0 | 17 | 0.4855 | 0.7578 |
| 0.2532 | 2.0 | 34 | 0.3632 | 0.8509 |
| 0.2351 | 3.0 | 51 | 0.3773 | 0.8509 |
| 0.043 | 4.0 | 68 | 0.3553 | 0.8571 |
| 0.08 | 5.0 | 85 | 0.4682 | 0.8447 |
| 0.3089 | 6.0 | 102 | 0.4686 | 0.8509 |
| 0.035 | 7.0 | 119 | 0.5876 | 0.8323 |
| 0.0188 | 8.0 | 136 | 0.5469 | 0.8571 |
| 0.021 | 9.0 | 153 | 0.5022 | 0.8447 |
| 0.0533 | 10.0 | 170 | 0.5240 | 0.8385 |
| 0.0175 | 11.0 | 187 | 0.6352 | 0.8447 |
| 0.0106 | 12.0 | 204 | 0.5856 | 0.8447 |
| 1.9534 | 13.0 | 221 | 0.5938 | 0.8509 |
| 0.0143 | 14.0 | 238 | 0.6074 | 0.8447 |
| 0.0079 | 15.0 | 255 | 0.6084 | 0.8447 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.2
|