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-7labels
results: []
financial-twhin-bert-large-7labels
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: 0.2960
- Accuracy: 0.9023
- F1: 0.9014
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: 2.1732582582331977e-05
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0082 | 0.3272 | 1500 | 0.4766 | 0.8302 | 0.8179 |
| 0.4866 | 0.6545 | 3000 | 0.4327 | 0.8552 | 0.8395 |
| 0.4354 | 0.9817 | 4500 | 0.3823 | 0.8616 | 0.8532 |
| 0.3368 | 1.3089 | 6000 | 0.3435 | 0.8875 | 0.8787 |
| 0.3136 | 1.6361 | 7500 | 0.3266 | 0.8872 | 0.8902 |
| 0.2829 | 1.9634 | 9000 | 0.2997 | 0.8950 | 0.8939 |
| 0.246 | 2.2906 | 10500 | 0.3183 | 0.8976 | 0.8923 |
| 0.2277 | 2.6178 | 12000 | 0.3090 | 0.8994 | 0.8978 |
| 0.2173 | 2.9450 | 13500 | 0.2960 | 0.9023 | 0.9014 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1