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# distilbert-amazon-shoe-review

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9690
- Accuracy: 0.5695
- F1: [0.62933333 0.43899923 0.48862216 0.54586923 0.73624476]
- Precision: [0.6096759  0.45826602 0.47939156 0.57317722 0.71149261]
- Recall: [0.6503006  0.42128713 0.4982152  0.52104499 0.76278119]

## 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: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1                                                       | Precision                                                | Recall                                                   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
| 0.9781        | 1.0   | 704  | 0.9690          | 0.5695   | [0.62933333 0.43899923 0.48862216 0.54586923 0.73624476] | [0.6096759  0.45826602 0.47939156 0.57317722 0.71149261] | [0.6503006  0.42128713 0.4982152  0.52104499 0.76278119] |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "distilbert-amazon-shoe-review", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-amazon-shoe-review
=============================


This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9690
* Accuracy: 0.5695
* F1: [0.62933333 0.43899923 0.48862216 0.54586923 0.73624476]
* Precision: [0.6096759 0.45826602 0.47939156 0.57317722 0.71149261]
* Recall: [0.6503006 0.42128713 0.4982152 0.52104499 0.76278119]


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: 128
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2