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# distilbert-amazon-shoe-reviews

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: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506  0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75      ]

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

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




# distilbert-amazon-shoe-reviews

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: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506  0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75      ]

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

# distilbert-amazon-shoe-reviews

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: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506  0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75      ] ## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # distilbert-amazon-shoe-reviews

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: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506  0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75      ] ## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
passage: TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# distilbert-amazon-shoe-reviews

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: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506  0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75      ]## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1### Training results### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3