File size: 1,746 Bytes
e0e3d4c f0765d2 e0e3d4c f0765d2 e0e3d4c f0765d2 e0e3d4c ef3f7b9 e0e3d4c f0765d2 e0e3d4c f0765d2 |
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 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-quora-insincere
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. -->
# distilbert-base-uncased-finetuned-quora-insincere
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [quora-insincere](https://huggingface.co/datasets/UKPLab/insincere-questions) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0946
- Accuracy: 0.9676
- F1 Score: 0.7309
## Model description
LABEL_0 = Sincere question
LABEL_1 = Insincere question
## 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: 2e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.093 | 1.0 | 62807 | 0.0859 | 0.9644 |
| 0.0695 | 2.0 | 125614 | 0.0946 | 0.9676 |
### Evaluation results
'eval_loss': 0.09461139887571335,
'eval_accuracy': 0.9676,
'eval_f1': 0.7308970099667774,
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1 |