metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- eoir_privacy
metrics:
- accuracy
- f1
model-index:
- name: bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: eoir_privacy
type: eoir_privacy
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.9175035868005739
- name: F1
type: f1
value: 0.8092868988391376
bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy
This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the eoir_privacy dataset. It achieves the following results on the evaluation set:
- Loss: 0.2159
- Accuracy: 0.9175
- F1: 0.8093
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 63 | 0.2343 | 0.9125 | 0.7953 |
No log | 2.0 | 126 | 0.2269 | 0.9110 | 0.8006 |
No log | 3.0 | 189 | 0.2159 | 0.9175 | 0.8093 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1