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# bert-base-banking77-pt2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the banking77 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3261
- F1: 0.9360

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5369        | 1.0   | 2501 | 0.4475          | 0.8808 |
| 0.2189        | 2.0   | 5002 | 0.3341          | 0.9290 |
| 0.1552        | 3.0   | 7503 | 0.3261          | 0.9360 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["banking77"], "metrics": ["f1"], "model-index": [{"name": "bert-base-banking77-pt2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "banking77", "type": "banking77", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "f1", "value": 0.9360461829994651, "name": "F1"}]}]}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:banking77 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-banking77 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-base-banking77-pt2
=======================


This model is a fine-tuned version of bert-base-uncased on the banking77 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3261
* F1: 0.9360


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: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-banking77 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-banking77 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.11.0