
<!-- 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. -->

# finbert-finetuned-FG-SINGLE_SENTENCE-NEWS

This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2997
- Accuracy: 0.6414
- F1: 0.6295

## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 321  | 0.9371          | 0.5699   | 0.4333 |
| 0.9282        | 2.0   | 642  | 0.9135          | 0.5930   | 0.5447 |
| 0.9282        | 3.0   | 963  | 0.9900          | 0.6033   | 0.5823 |
| 0.6743        | 4.0   | 1284 | 1.0802          | 0.6142   | 0.6065 |
| 0.3134        | 5.0   | 1605 | 1.5156          | 0.6183   | 0.5971 |
| 0.3134        | 6.0   | 1926 | 1.3695          | 0.6319   | 0.6183 |
| 0.1709        | 7.0   | 2247 | 1.8746          | 0.6462   | 0.6267 |
| 0.1112        | 8.0   | 2568 | 2.0880          | 0.6176   | 0.6155 |
| 0.1112        | 9.0   | 2889 | 2.3953          | 0.6190   | 0.6087 |
| 0.0811        | 10.0  | 3210 | 2.3792          | 0.6339   | 0.6225 |
| 0.0608        | 11.0  | 3531 | 2.3783          | 0.6360   | 0.6282 |
| 0.0608        | 12.0  | 3852 | 2.5982          | 0.6544   | 0.6351 |
| 0.039         | 13.0  | 4173 | 2.7687          | 0.6346   | 0.6305 |
| 0.039         | 14.0  | 4494 | 2.8980          | 0.6414   | 0.6299 |
| 0.0206        | 15.0  | 4815 | 3.0858          | 0.6319   | 0.6253 |
| 0.0168        | 16.0  | 5136 | 3.2408          | 0.6244   | 0.6170 |
| 0.0168        | 17.0  | 5457 | 3.1809          | 0.6435   | 0.6293 |
| 0.0123        | 18.0  | 5778 | 3.2629          | 0.6449   | 0.6324 |
| 0.0055        | 19.0  | 6099 | 3.2866          | 0.6449   | 0.6308 |
| 0.0055        | 20.0  | 6420 | 3.2997          | 0.6414   | 0.6295 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "finbert-finetuned-FG-SINGLE_SENTENCE-NEWS", "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 

finbert-finetuned-FG-SINGLE\_SENTENCE-NEWS
==========================================


This model is a fine-tuned version of ProsusAI/finbert on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.2997
* Accuracy: 0.6414
* F1: 0.6295


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: 6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6
passage: 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: 6e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.16.2
* Pytorch 1.9.1
* Datasets 1.18.4
* Tokenizers 0.11.6