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license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model
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. -->
# model
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6917
- Precision: 0.7168
- Recall: 0.7053
- F1: 0.7088
- Accuracy: 0.726
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9791 | 1.0 | 1489 | 0.8084 | 0.6198 | 0.6089 | 0.6093 | 0.6385 |
| 0.8129 | 2.0 | 2978 | 0.7380 | 0.6635 | 0.6500 | 0.6531 | 0.6735 |
| 0.6937 | 3.0 | 4467 | 0.7328 | 0.6826 | 0.6716 | 0.6745 | 0.691 |
| 0.6002 | 4.0 | 5956 | 0.6901 | 0.7110 | 0.6951 | 0.6973 | 0.7205 |
| 0.5362 | 5.0 | 7445 | 0.6917 | 0.7168 | 0.7053 | 0.7088 | 0.726 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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