metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_BERT_token_itr0_0.0001_all_01_03_2022-15_52_19
results: []
correct_BERT_token_itr0_0.0001_all_01_03_2022-15_52_19
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: 0.2711
- Precision: 0.3373
- Recall: 0.5670
- F1: 0.4230
- Accuracy: 0.8943
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: 0.0001
- 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 | 0.3783 | 0.1833 | 0.3975 | 0.2509 | 0.8413 |
No log | 2.0 | 60 | 0.3021 | 0.3280 | 0.4820 | 0.3904 | 0.8876 |
No log | 3.0 | 90 | 0.3196 | 0.3504 | 0.5036 | 0.4133 | 0.8918 |
No log | 4.0 | 120 | 0.3645 | 0.3434 | 0.5306 | 0.4170 | 0.8759 |
No log | 5.0 | 150 | 0.4027 | 0.3217 | 0.5486 | 0.4056 | 0.8797 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3