metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10
results: []
bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2741
- Precision: 0.1936
- Recall: 0.3243
- F1: 0.2424
- Accuracy: 0.8764
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: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 30 | 0.3235 | 0.1062 | 0.2076 | 0.1405 | 0.8556 |
| No log | 2.0 | 60 | 0.2713 | 0.1710 | 0.3080 | 0.2199 | 0.8872 |
| No log | 3.0 | 90 | 0.3246 | 0.2010 | 0.3391 | 0.2524 | 0.8334 |
| No log | 4.0 | 120 | 0.3008 | 0.2011 | 0.3685 | 0.2602 | 0.8459 |
| No log | 5.0 | 150 | 0.2714 | 0.1780 | 0.3772 | 0.2418 | 0.8661 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3