metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ST_DA_100_v2
results: []
BERT_ST_DA_100_v2
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2371
- Precision: 0.9457
- Recall: 0.9480
- F1: 0.9469
- Accuracy: 0.9446
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 59 | 0.3489 | 0.9065 | 0.9194 | 0.9129 | 0.9085 |
| No log | 2.0 | 118 | 0.2883 | 0.9190 | 0.9267 | 0.9228 | 0.9180 |
| No log | 3.0 | 177 | 0.2505 | 0.9322 | 0.9403 | 0.9362 | 0.9330 |
| No log | 4.0 | 236 | 0.2300 | 0.9384 | 0.9446 | 0.9415 | 0.9384 |
| No log | 5.0 | 295 | 0.2305 | 0.9397 | 0.9435 | 0.9416 | 0.9386 |
| No log | 6.0 | 354 | 0.2332 | 0.9443 | 0.9482 | 0.9462 | 0.9438 |
| No log | 7.0 | 413 | 0.2341 | 0.9433 | 0.9468 | 0.9450 | 0.9429 |
| No log | 8.0 | 472 | 0.2364 | 0.9441 | 0.9474 | 0.9457 | 0.9430 |
| 0.1814 | 9.0 | 531 | 0.2339 | 0.9457 | 0.9472 | 0.9465 | 0.9439 |
| 0.1814 | 10.0 | 590 | 0.2371 | 0.9457 | 0.9480 | 0.9469 | 0.9446 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1