File size: 2,894 Bytes
6899c63 |
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 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- filter_v2
metrics:
- f1
- accuracy
model-index:
- name: favs_filter_classification_v2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: filter_v2
type: filter_v2
config: default
split: train
args: default
metrics:
- name: F1
type: f1
value: 1.0
- name: Accuracy
type: accuracy
value: 1.0
---
<!-- 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. -->
# favs_filter_classification_v2
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2580
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0
## 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: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6752 | 1.0 | 13 | 0.6166 | 0.3810 | 0.5772 | 0.0 |
| 0.5905 | 2.0 | 26 | 0.5326 | 0.6286 | 0.7399 | 0.3636 |
| 0.5004 | 3.0 | 39 | 0.4812 | 0.5 | 0.6636 | 0.2727 |
| 0.4268 | 4.0 | 52 | 0.4346 | 0.7027 | 0.7899 | 0.4545 |
| 0.391 | 5.0 | 65 | 0.4072 | 0.8205 | 0.8737 | 0.5455 |
| 0.3725 | 6.0 | 78 | 0.3666 | 0.8108 | 0.8575 | 0.6364 |
| 0.3215 | 7.0 | 91 | 0.3382 | 0.8889 | 0.9 | 0.7273 |
| 0.3094 | 8.0 | 104 | 0.3083 | 0.9474 | 0.95 | 0.8182 |
| 0.2825 | 9.0 | 117 | 0.2925 | 0.9189 | 0.925 | 0.7273 |
| 0.2596 | 10.0 | 130 | 0.2801 | 0.9474 | 0.95 | 0.8182 |
| 0.2517 | 11.0 | 143 | 0.2580 | 1.0 | 1.0 | 1.0 |
| 0.2308 | 12.0 | 156 | 0.2538 | 0.9744 | 0.975 | 0.9091 |
| 0.238 | 13.0 | 169 | 0.2459 | 0.9744 | 0.975 | 0.9091 |
| 0.2194 | 14.0 | 182 | 0.2379 | 1.0 | 1.0 | 1.0 |
| 0.2181 | 15.0 | 195 | 0.2366 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
|