metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-uncased_08112024T144127
results: []
bert-base-uncased_08112024T144127
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: 0.4242
- F1: 0.8849
- Learning Rate: 0.0
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 600
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Rate |
|---|---|---|---|---|---|
| No log | 0.9942 | 86 | 1.7911 | 0.1661 | 0.0000 |
| No log | 2.0 | 173 | 1.6895 | 0.2558 | 0.0000 |
| No log | 2.9942 | 259 | 1.5467 | 0.4336 | 0.0000 |
| No log | 4.0 | 346 | 1.3716 | 0.5012 | 0.0000 |
| No log | 4.9942 | 432 | 1.1818 | 0.5459 | 0.0000 |
| 1.5117 | 6.0 | 519 | 1.0336 | 0.5938 | 0.0000 |
| 1.5117 | 6.9942 | 605 | 0.9389 | 0.6309 | 1e-05 |
| 1.5117 | 8.0 | 692 | 0.8480 | 0.6802 | 0.0000 |
| 1.5117 | 8.9942 | 778 | 0.7481 | 0.7288 | 0.0000 |
| 1.5117 | 10.0 | 865 | 0.6824 | 0.7561 | 0.0000 |
| 1.5117 | 10.9942 | 951 | 0.6213 | 0.7867 | 0.0000 |
| 0.7682 | 12.0 | 1038 | 0.5781 | 0.8039 | 0.0000 |
| 0.7682 | 12.9942 | 1124 | 0.5184 | 0.8345 | 0.0000 |
| 0.7682 | 14.0 | 1211 | 0.4854 | 0.8489 | 0.0000 |
| 0.7682 | 14.9942 | 1297 | 0.4815 | 0.8559 | 0.0000 |
| 0.7682 | 16.0 | 1384 | 0.4422 | 0.8704 | 0.0000 |
| 0.7682 | 16.9942 | 1470 | 0.4422 | 0.8761 | 6e-06 |
| 0.305 | 18.0 | 1557 | 0.4368 | 0.8791 | 0.0000 |
| 0.305 | 18.9942 | 1643 | 0.4242 | 0.8849 | 0.0000 |
| 0.305 | 20.0 | 1730 | 0.4483 | 0.8829 | 0.0000 |
| 0.305 | 20.9942 | 1816 | 0.4539 | 0.8841 | 0.0000 |
| 0.305 | 22.0 | 1903 | 0.4521 | 0.8862 | 0.0000 |
| 0.305 | 22.9942 | 1989 | 0.4450 | 0.8896 | 0.0000 |
| 0.1014 | 24.0 | 2076 | 0.4603 | 0.8874 | 0.0000 |
| 0.1014 | 24.9942 | 2162 | 0.4750 | 0.8864 | 0.0000 |
| 0.1014 | 26.0 | 2249 | 0.4711 | 0.8887 | 7e-07 |
| 0.1014 | 26.9942 | 2335 | 0.4756 | 0.8879 | 4e-07 |
| 0.1014 | 28.0 | 2422 | 0.4691 | 0.8883 | 2e-07 |
| 0.0521 | 28.9942 | 2508 | 0.4694 | 0.8883 | 0.0 |
| 0.0521 | 29.8266 | 2580 | 0.4699 | 0.8883 | 0.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1