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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Raffel_bert_emotion_classification
results: []
---
<!-- 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. -->
# Raffel_bert_emotion_classification
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3423
- Accuracy: 0.9596
I train this model from kaggle dataset, you can access the dataset via this link : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset
## 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: 4e-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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 167 | 0.1212 | 0.9579 |
| No log | 2.0 | 334 | 0.1362 | 0.9596 |
| 0.1622 | 3.0 | 501 | 0.2034 | 0.9596 |
| 0.1622 | 4.0 | 668 | 0.2035 | 0.9630 |
| 0.1622 | 5.0 | 835 | 0.2153 | 0.9630 |
| 0.017 | 6.0 | 1002 | 0.2010 | 0.9613 |
| 0.017 | 7.0 | 1169 | 0.2718 | 0.9579 |
| 0.017 | 8.0 | 1336 | 0.2641 | 0.9613 |
| 0.0099 | 9.0 | 1503 | 0.2524 | 0.9613 |
| 0.0099 | 10.0 | 1670 | 0.2918 | 0.9579 |
| 0.0099 | 11.0 | 1837 | 0.2749 | 0.9562 |
| 0.0029 | 12.0 | 2004 | 0.3133 | 0.9562 |
| 0.0029 | 13.0 | 2171 | 0.2952 | 0.9579 |
| 0.0029 | 14.0 | 2338 | 0.3334 | 0.9596 |
| 0.0022 | 15.0 | 2505 | 0.3286 | 0.9596 |
| 0.0022 | 16.0 | 2672 | 0.3340 | 0.9596 |
| 0.0022 | 17.0 | 2839 | 0.3344 | 0.9596 |
| 0.0013 | 18.0 | 3006 | 0.3395 | 0.9596 |
| 0.0013 | 19.0 | 3173 | 0.3423 | 0.9596 |
| 0.0013 | 20.0 | 3340 | 0.3423 | 0.9596 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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