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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_us_reviews
metrics:
- accuracy
model-index:
- name: test_trainer
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_us_reviews
type: amazon_us_reviews
config: Books_v1_01
split: train[:1%]
args: Books_v1_01
metrics:
- name: Accuracy
type: accuracy
value: 0.7441424554826617
---
<!-- 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. -->
# test_trainer
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the amazon_us_reviews dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9348
- Accuracy: 0.7441
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6471 | 1.0 | 7500 | 0.6596 | 0.7376 |
| 0.5235 | 2.0 | 15000 | 0.6997 | 0.7423 |
| 0.3955 | 3.0 | 22500 | 0.9348 | 0.7441 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2