metadata
license: apache-2.0
base_model: Twitter/twhin-bert-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: financial-twhin-bert-large-3labels-test1
results: []
financial-twhin-bert-large-3labels-test1
This model is a fine-tuned version of Twitter/twhin-bert-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3334
- Accuracy: 0.8826
- F1: 0.8823
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: 9.656814753771254e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 1203
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9822 | 0.1550 | 100 | 0.7065 | 0.6772 | 0.5469 |
| 0.7307 | 0.3101 | 200 | 0.5716 | 0.7471 | 0.7179 |
| 0.6482 | 0.4651 | 300 | 0.5388 | 0.7716 | 0.7493 |
| 0.6008 | 0.6202 | 400 | 0.4300 | 0.8494 | 0.8446 |
| 0.5237 | 0.7752 | 500 | 0.4190 | 0.8343 | 0.8401 |
| 0.5106 | 0.9302 | 600 | 0.4114 | 0.8444 | 0.8404 |
| 0.4832 | 1.0853 | 700 | 0.3865 | 0.8545 | 0.8596 |
| 0.4031 | 1.2403 | 800 | 0.3741 | 0.8602 | 0.8653 |
| 0.3729 | 1.3953 | 900 | 0.3334 | 0.8826 | 0.8823 |
| 0.3661 | 1.5504 | 1000 | 0.3494 | 0.8725 | 0.8750 |
| 0.332 | 1.7054 | 1100 | 0.3390 | 0.8725 | 0.8753 |
| 0.3637 | 1.8605 | 1200 | 0.3386 | 0.8689 | 0.8724 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1