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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base-finetuned-3d-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-3d-sentiment
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5817
- Accuracy: 0.7753
- Precision: 0.7757
- Recall: 0.7753
- F1: 0.7745
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 6381
- num_epochs: 7
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.7758 | 1.0 | 1595 | 0.7691 | 0.7069 | 0.7256 | 0.7069 | 0.7052 |
| 0.5496 | 2.0 | 3190 | 0.6961 | 0.7255 | 0.7441 | 0.7255 | 0.7252 |
| 0.4856 | 3.0 | 4785 | 0.6451 | 0.7368 | 0.7562 | 0.7368 | 0.7328 |
| 0.4257 | 4.0 | 6380 | 0.5817 | 0.7753 | 0.7757 | 0.7753 | 0.7745 |
| 0.351 | 5.0 | 7975 | 0.6637 | 0.7633 | 0.7717 | 0.7633 | 0.7637 |
| 0.2551 | 6.0 | 9570 | 0.7646 | 0.7696 | 0.7738 | 0.7696 | 0.7699 |
| 0.1845 | 7.0 | 11165 | 0.8529 | 0.7674 | 0.7730 | 0.7674 | 0.7680 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3
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