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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-sentiment-bert-base-uncased-6000-samples
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: 0.7678571428571429
- name: F1
type: f1
value: 0.7167992873886065
---
<!-- 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-sentiment-bert-base-uncased-6000-samples
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: 0.5890
- Accuracy: 0.7679
- F1: 0.7168
## Predicted labels
- LABEL_0: Negative review
- LABEL_1: Neutral review
- LABEL_2: Positive review
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 188 | 0.5745 | 0.7586 | 0.7149 |
| No log | 2.0 | 376 | 0.5890 | 0.7679 | 0.7168 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3
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