metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- inspec
metrics:
- f1
model-index:
- name: bert-finetuned-inspec
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: inspec
type: inspec
args: extraction
metrics:
- name: F1
type: f1
value: 0.30353331752430635
bert-finetuned-inspec
This model is a fine-tuned version of bert-base-uncased on the inspec dataset. It achieves the following results on the evaluation set:
- Loss: 0.3055
- F1: 0.3035
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.3323 | 1.0 | 125 | 0.2799 | 0.1521 |
| 0.2563 | 2.0 | 250 | 0.2638 | 0.2230 |
| 0.2179 | 3.0 | 375 | 0.2689 | 0.2607 |
| 0.1809 | 4.0 | 500 | 0.2807 | 0.3122 |
| 0.1545 | 5.0 | 625 | 0.3055 | 0.3035 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1