---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# financial-twhin-bert-large-3labels-test1

This model is a fine-tuned version of [Twitter/twhin-bert-large](https://huggingface.co/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