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# finance_news_classifier

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1719
- Accuracy: 0.8680

## 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: 2e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 243  | 0.4023          | 0.8412   |
| No log        | 2.0   | 486  | 0.4435          | 0.8526   |
| 0.3668        | 3.0   | 729  | 0.5688          | 0.8402   |
| 0.3668        | 4.0   | 972  | 0.6626          | 0.8598   |
| 0.1479        | 5.0   | 1215 | 0.8238          | 0.8557   |
| 0.1479        | 6.0   | 1458 | 0.9073          | 0.8536   |
| 0.0654        | 7.0   | 1701 | 0.9993          | 0.8557   |
| 0.0654        | 8.0   | 1944 | 1.0495          | 0.8526   |
| 0.0368        | 9.0   | 2187 | 1.1007          | 0.8392   |
| 0.0368        | 10.0  | 2430 | 1.1122          | 0.8505   |
| 0.0212        | 11.0  | 2673 | 1.1024          | 0.8680   |
| 0.0212        | 12.0  | 2916 | 1.0697          | 0.8670   |
| 0.0148        | 13.0  | 3159 | 1.1283          | 0.8639   |
| 0.0148        | 14.0  | 3402 | 1.1176          | 0.8701   |
| 0.008         | 15.0  | 3645 | 1.1625          | 0.8660   |
| 0.008         | 16.0  | 3888 | 1.1794          | 0.8639   |
| 0.0052        | 17.0  | 4131 | 1.1701          | 0.8629   |
| 0.0052        | 18.0  | 4374 | 1.1919          | 0.8608   |
| 0.005         | 19.0  | 4617 | 1.1745          | 0.8670   |
| 0.005         | 20.0  | 4860 | 1.1719          | 0.8680   |


### Framework versions

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

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "finance_news_classifier", "results": []}]}
transformers pytorch tensorboard safetensors xlm-roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #xlm-roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

finance\_news\_classifier
=========================


This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.1719
* Accuracy: 0.8680


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: 2e-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: 20


### 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: 2e-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: 20 ### 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 #safetensors #xlm-roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 20 ### Training results ### Framework versions


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