metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-tokenCLS-CATALYST
results: []
bert-base-cased-tokenCLS-CATALYST
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0783
- Precision: 0.6142
- Recall: 0.8261
- F1: 0.7046
- Accuracy: 0.9749
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
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1022 | 1.0 | 1114 | 0.0938 | 0.5462 | 0.7536 | 0.6334 | 0.9704 |
| 0.0635 | 2.0 | 2228 | 0.1003 | 0.6086 | 0.8609 | 0.7131 | 0.9758 |
| 0.0504 | 3.0 | 3342 | 0.0783 | 0.6142 | 0.8261 | 0.7046 | 0.9749 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3