metadata
language:
- mn
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-fine-tuning-demo
results: []
bert-fine-tuning-demo
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: 0.5272
- Precision: 0.3328
- Recall: 0.1317
- F1: 0.1888
- Accuracy: 0.8546
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: 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 |
|---|---|---|---|---|---|---|---|
| 0.5529 | 1.0 | 953 | 0.5345 | 0.3217 | 0.1220 | 0.1769 | 0.8535 |
| 0.546 | 2.0 | 1906 | 0.5290 | 0.3320 | 0.1301 | 0.1869 | 0.8544 |
| 0.5432 | 3.0 | 2859 | 0.5272 | 0.3328 | 0.1317 | 0.1888 | 0.8546 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1