---
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-pesudo
  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-dev2

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: 0.3035
- Accuracy: 0.8948
- F1: 0.8932

## 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: 3.671821890679145e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8977        | 0.15  | 100  | 0.6404          | 0.7428   | 0.6732 |
| 0.7036        | 0.3   | 200  | 0.8094          | 0.6326   | 0.6576 |
| 0.6344        | 0.46  | 300  | 0.5222          | 0.7961   | 0.8068 |
| 0.5275        | 0.61  | 400  | 0.4322          | 0.8372   | 0.8425 |
| 0.4899        | 0.76  | 500  | 0.5061          | 0.8249   | 0.8320 |
| 0.4723        | 0.91  | 600  | 0.3711          | 0.8631   | 0.8577 |
| 0.4345        | 1.06  | 700  | 0.3421          | 0.8833   | 0.8819 |
| 0.3524        | 1.21  | 800  | 0.3322          | 0.8811   | 0.8829 |
| 0.3288        | 1.37  | 900  | 0.4062          | 0.8696   | 0.8724 |
| 0.3566        | 1.52  | 1000 | 0.3035          | 0.8948   | 0.8932 |
| 0.3253        | 1.67  | 1100 | 0.3064          | 0.8934   | 0.8938 |
| 0.2861        | 1.82  | 1200 | 0.3336          | 0.8927   | 0.8932 |
| 0.2955        | 1.97  | 1300 | 0.3526          | 0.8970   | 0.8959 |
| 0.1759        | 2.12  | 1400 | 0.4498          | 0.8948   | 0.8942 |
| 0.171         | 2.28  | 1500 | 0.3863          | 0.8955   | 0.8950 |
| 0.1636        | 2.43  | 1600 | 0.4361          | 0.8869   | 0.8889 |
| 0.1431        | 2.58  | 1700 | 0.4124          | 0.8963   | 0.8967 |
| 0.1661        | 2.73  | 1800 | 0.4062          | 0.8984   | 0.8989 |
| 0.1549        | 2.88  | 1900 | 0.4041          | 0.8999   | 0.9002 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2