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# twiiter_try15_fold3

This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1796
- F1: 0.9805

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2022        | 1.0   | 500  | 0.1547          | 0.9636 |
| 0.0612        | 2.0   | 1000 | 0.2014          | 0.9660 |
| 0.0211        | 3.0   | 1500 | 0.1204          | 0.9776 |
| 0.0107        | 4.0   | 2000 | 0.1797          | 0.9745 |
| 0.0073        | 5.0   | 2500 | 0.1931          | 0.9752 |
| 0.0128        | 6.0   | 3000 | 0.1808          | 0.9741 |
| 0.0088        | 7.0   | 3500 | 0.1756          | 0.9750 |
| 0.0088        | 8.0   | 4000 | 0.1726          | 0.9781 |
| 0.0012        | 9.0   | 4500 | 0.1707          | 0.9785 |
| 0.0004        | 10.0  | 5000 | 0.1794          | 0.9780 |
| 0.0031        | 11.0  | 5500 | 0.2156          | 0.9743 |
| 0.0012        | 12.0  | 6000 | 0.2106          | 0.9741 |
| 0.0           | 13.0  | 6500 | 0.1925          | 0.9796 |
| 0.0           | 14.0  | 7000 | 0.1903          | 0.9789 |
| 0.0008        | 15.0  | 7500 | 0.1796          | 0.9805 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "twiiter_try15_fold3", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

twiiter\_try15\_fold3
=====================


This model is a fine-tuned version of ProsusAI/finbert on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1796
* F1: 0.9805


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: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3