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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-amazon-shoe-reviews
results:
- task:
type: text-classification
name: Text Classification
dataset:
type: amazon_us_reviews
name: Amazon US reviews
split: Shoes
metrics:
- type: accuracy
value: 0.48
name: Accuracy
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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: 1.3445
- Accuracy: 0.48
- F1: [0. 0. 0. 0. 0.64864865]
- Precision: [0. 0. 0. 0. 0.48]
- Recall: [0. 0. 0. 0. 1.]
## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------:|:----------------:|
| No log | 1.0 | 15 | 1.3445 | 0.48 | [0. 0. 0. 0. 0.64864865] | [0. 0. 0. 0. 0.48] | [0. 0. 0. 0. 1.] |
### Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1