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# bert-large-uncased-financial-phrasebank-allagree2

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0734
- Accuracy: 0.9912
- F1: 0.9911

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3209        | 1.0   | 227  | 0.1929          | 0.9558   | 0.9551 |
| 0.0821        | 2.0   | 454  | 0.0994          | 0.9867   | 0.9867 |
| 0.04          | 3.0   | 681  | 0.0685          | 0.9867   | 0.9866 |
| 0.0098        | 4.0   | 908  | 0.0980          | 0.9867   | 0.9867 |
| 0.0003        | 5.0   | 1135 | 0.0734          | 0.9912   | 0.9911 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["financial_phrasebank"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "bert-large-uncased-financial-phrasebank-allagree2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "financial_phrasebank", "type": "financial_phrasebank", "config": "sentences_allagree", "split": "train", "args": "sentences_allagree"}, "metrics": [{"type": "accuracy", "value": 0.9911504424778761, "name": "Accuracy"}, {"type": "f1", "value": 0.9910704012566471, "name": "F1"}]}]}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:financial_phrasebank license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-financial_phrasebank #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-large-uncased-financial-phrasebank-allagree2
=================================================


This model is a fine-tuned version of bert-large-uncased on the financial\_phrasebank dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0734
* Accuracy: 0.9912
* F1: 0.9911


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-financial_phrasebank #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-financial_phrasebank #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1