Mehdi009's picture
Fine tune for the antisemtism harassment detection
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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
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. -->
# results
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: 0.4186
- Accuracy: 0.9028
- Precision: 0.7440
- Recall: 0.6525
- F1: 0.6953
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.238 | 1.0 | 347 | 0.2861 | 0.8913 | 0.7179 | 0.5932 | 0.6497 |
| 0.2052 | 2.0 | 694 | 0.2654 | 0.9057 | 0.7966 | 0.5975 | 0.6828 |
| 0.024 | 3.0 | 1041 | 0.4186 | 0.9028 | 0.7440 | 0.6525 | 0.6953 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Tokenizers 0.19.1