bert-base-uncased-issue-128
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: 1.2410
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0992 | 1.0 | 291 | 1.7045 |
| 1.6312 | 2.0 | 582 | 1.5191 |
| 1.493 | 3.0 | 873 | 1.3559 |
| 1.4017 | 4.0 | 1164 | 1.3378 |
| 1.3391 | 5.0 | 1455 | 1.2504 |
| 1.2695 | 6.0 | 1746 | 1.3550 |
| 1.222 | 7.0 | 2037 | 1.3009 |
| 1.2078 | 8.0 | 2328 | 1.3408 |
| 1.1816 | 9.0 | 2619 | 1.2148 |
| 1.1352 | 10.0 | 2910 | 1.1639 |
| 1.1311 | 11.0 | 3201 | 1.1334 |
| 1.103 | 12.0 | 3492 | 1.1944 |
| 1.0915 | 13.0 | 3783 | 1.2266 |
| 1.0766 | 14.0 | 4074 | 1.2206 |
| 1.072 | 15.0 | 4365 | 1.2132 |
| 1.0515 | 16.0 | 4656 | 1.2410 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for Shawn156/bert-base-uncased-issue-128
Base model
google-bert/bert-base-uncased