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# distilbert-base-uncased-finetuned-banking77

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the banking77 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2935
- Accuracy: 0.925
- F1: 0.9250

## 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: 9.686210354742596e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 40
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 126  | 1.1457          | 0.7896   | 0.7685 |
| No log        | 2.0   | 252  | 0.4673          | 0.8906   | 0.8889 |
| No log        | 3.0   | 378  | 0.3488          | 0.9150   | 0.9151 |
| 0.9787        | 4.0   | 504  | 0.3238          | 0.9180   | 0.9179 |
| 0.9787        | 5.0   | 630  | 0.3126          | 0.9225   | 0.9226 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6

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transformers pytorch safetensors distilbert text-classification generated_from_trainer dataset:banking77 base_model:distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-banking77 #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased-finetuned-banking77
===========================================


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


* Loss: 0.2935
* Accuracy: 0.925
* F1: 0.9250


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: 9.686210354742596e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9.686210354742596e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-banking77 #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9.686210354742596e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-banking77 #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9.686210354742596e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6