metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- inspec
metrics:
- f1
- precision
- recall
model-index:
- name: bert-finetuned-inspec-3-epochs
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: inspec
type: inspec
args: extraction
metrics:
- name: F1
type: f1
value: 0.28328008519701814
- name: Precision
type: precision
value: 0.26594090202177295
- name: Recall
type: recall
value: 0.3030379746835443
bert-finetuned-inspec-3-epochs
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: 0.2728
- F1: 0.2833
- Precision: 0.2659
- Recall: 0.3030
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: 0
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.3338 | 1.0 | 125 | 0.2837 | 0.1401 | 0.1510 | 0.1306 |
| 0.2575 | 2.0 | 250 | 0.2658 | 0.2183 | 0.2519 | 0.1927 |
| 0.2259 | 3.0 | 375 | 0.2728 | 0.2833 | 0.2659 | 0.3030 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1