README.md

---
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
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# 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: 0.6047
- Accuracy: 0.7713
- Precision: 0.7719
- Recall: 0.7713
- F1: 0.7703

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.7978        | 1.0   | 1595 | 0.7782          | 0.6953   | 0.7191    | 0.6953 | 0.6926 |
| 0.5526        | 2.0   | 3190 | 0.6951          | 0.7229   | 0.7398    | 0.7229 | 0.7233 |
| 0.4904        | 3.0   | 4785 | 0.6390          | 0.7388   | 0.7530    | 0.7388 | 0.7366 |
| 0.4307        | 4.0   | 6380 | 0.6047          | 0.7713   | 0.7719    | 0.7713 | 0.7703 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3