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---
library_name: transformers
language:
- en
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sentiment
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. -->
# roberta-base-finetuned-sentiment
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb-dataset-of-50k-movie-reviews dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2595
- Accuracy: 0.9495
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2815 | 1.0 | 1250 | 0.1705 | 0.9366 |
| 0.1358 | 2.0 | 2500 | 0.1550 | 0.9463 |
| 0.0879 | 3.0 | 3750 | 0.2081 | 0.947 |
| 0.0564 | 4.0 | 5000 | 0.2479 | 0.9474 |
| 0.0339 | 5.0 | 6250 | 0.2595 | 0.9495 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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