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End of training
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---
license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
- f1
model-index:
- name: amazon-reviews-finetuning-bert-base-sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: amazon_reviews_multi
config: en
split: validation
args: en
metrics:
- name: Accuracy
type: accuracy
value: 0.5764
- name: F1
type: f1
value: 0.5738591890717804
---
<!-- 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. -->
# amazon-reviews-finetuning-bert-base-sentiment
This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0136
- Accuracy: 0.5764
- F1: 0.5739
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9867 | 1.0 | 1563 | 0.9814 | 0.5792 | 0.5677 |
| 0.8435 | 2.0 | 3126 | 1.0136 | 0.5764 | 0.5739 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3