metadata
license: apache-2.0
base_model: Twitter/twhin-bert-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: twhin-bert-base
results: []
twhin-bert-base
This model is a fine-tuned version of Twitter/twhin-bert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6341
- F1: 0.3077
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-07
- 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: 50
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
0.6867 | 1.0 | 189 | 0.6817 | 0.1026 |
0.684 | 2.0 | 378 | 0.6746 | 0.0571 |
0.675 | 3.0 | 567 | 0.6649 | 0.0 |
0.6642 | 4.0 | 756 | 0.6577 | 0.0 |
0.6653 | 5.0 | 945 | 0.6542 | 0.0 |
0.6649 | 6.0 | 1134 | 0.6479 | 0.0 |
0.6648 | 7.0 | 1323 | 0.6460 | 0.0 |
0.6511 | 8.0 | 1512 | 0.6387 | 0.0 |
0.6535 | 9.0 | 1701 | 0.6332 | 0.0 |
0.6544 | 10.0 | 1890 | 0.6261 | 0.0 |
0.6382 | 11.0 | 2079 | 0.6154 | 0.0 |
0.6315 | 12.0 | 2268 | 0.6051 | 0.0 |
0.6231 | 13.0 | 2457 | 0.5957 | 0.2326 |
0.603 | 14.0 | 2646 | 0.5858 | 0.2326 |
0.6034 | 15.0 | 2835 | 0.5771 | 0.2553 |
0.5938 | 16.0 | 3024 | 0.5694 | 0.2308 |
0.5884 | 17.0 | 3213 | 0.5642 | 0.3103 |
0.5763 | 18.0 | 3402 | 0.5611 | 0.3103 |
0.5675 | 19.0 | 3591 | 0.5641 | 0.2857 |
0.5672 | 20.0 | 3780 | 0.5598 | 0.3000 |
0.5674 | 21.0 | 3969 | 0.5579 | 0.2857 |
0.5479 | 22.0 | 4158 | 0.5642 | 0.3125 |
0.5621 | 23.0 | 4347 | 0.5688 | 0.2903 |
0.5516 | 24.0 | 4536 | 0.5685 | 0.3077 |
0.5597 | 25.0 | 4725 | 0.5713 | 0.3077 |
0.5418 | 26.0 | 4914 | 0.5761 | 0.3077 |
0.5477 | 27.0 | 5103 | 0.5752 | 0.3030 |
0.535 | 28.0 | 5292 | 0.5876 | 0.3077 |
0.5544 | 29.0 | 5481 | 0.5841 | 0.3030 |
0.5238 | 30.0 | 5670 | 0.5855 | 0.3030 |
0.5375 | 31.0 | 5859 | 0.5894 | 0.3030 |
0.5092 | 32.0 | 6048 | 0.5985 | 0.3077 |
0.5262 | 33.0 | 6237 | 0.5988 | 0.3077 |
0.5418 | 34.0 | 6426 | 0.6038 | 0.3077 |
0.531 | 35.0 | 6615 | 0.6087 | 0.3077 |
0.5627 | 36.0 | 6804 | 0.6064 | 0.3077 |
0.545 | 37.0 | 6993 | 0.6110 | 0.3077 |
0.5105 | 38.0 | 7182 | 0.6134 | 0.3077 |
0.5471 | 39.0 | 7371 | 0.6111 | 0.3077 |
0.5114 | 40.0 | 7560 | 0.6212 | 0.3077 |
0.5411 | 41.0 | 7749 | 0.6159 | 0.3077 |
0.5304 | 42.0 | 7938 | 0.6213 | 0.3077 |
0.5146 | 43.0 | 8127 | 0.6276 | 0.3077 |
0.5223 | 44.0 | 8316 | 0.6301 | 0.3077 |
0.5345 | 45.0 | 8505 | 0.6281 | 0.3077 |
0.5368 | 46.0 | 8694 | 0.6284 | 0.3077 |
0.516 | 47.0 | 8883 | 0.6320 | 0.3077 |
0.5241 | 48.0 | 9072 | 0.6339 | 0.3077 |
0.5267 | 49.0 | 9261 | 0.6342 | 0.3077 |
0.5478 | 50.0 | 9450 | 0.6341 | 0.3077 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3