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# deadlyhacker/investopedia_finbert

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:
- Train Loss: 1.2476
- Train Accuracy: 0.1092
- Validation Loss: 1.2565
- Validation Accuracy: 0.1097
- Epoch: 10

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.5600     | 0.0855         | 1.7046          | 0.1015              | 0     |
| 1.7150     | 0.1006         | 1.5251          | 0.1041              | 1     |
| 1.5635     | 0.1032         | 1.4501          | 0.1053              | 2     |
| 1.4843     | 0.1046         | 1.3938          | 0.1064              | 3     |
| 1.4215     | 0.1058         | 1.3624          | 0.1075              | 4     |
| 1.3870     | 0.1062         | 1.3373          | 0.1077              | 5     |
| 1.3483     | 0.1071         | 1.3053          | 0.1082              | 6     |
| 1.3187     | 0.1079         | 1.3033          | 0.1090              | 7     |
| 1.2964     | 0.1083         | 1.2965          | 0.1081              | 8     |
| 1.2720     | 0.1088         | 1.2652          | 0.1088              | 9     |
| 1.2476     | 0.1092         | 1.2565          | 0.1097              | 10    |


### Framework versions

- Transformers 4.29.1
- TensorFlow 2.10.1
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "deadlyhacker/investopedia_finbert", "results": []}]}
transformers tf bert fill-mask generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

deadlyhacker/investopedia\_finbert
==================================


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


* Train Loss: 1.2476
* Train Accuracy: 0.1092
* Validation Loss: 1.2565
* Validation Accuracy: 0.1097
* Epoch: 10


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:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.29.1
* TensorFlow 2.10.1
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.1
* TensorFlow 2.10.1
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.1
* TensorFlow 2.10.1
* Datasets 2.12.0
* Tokenizers 0.13.3