---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: distilroberta-base
model-index:
- name: distilroberta-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. -->

# distilroberta-base-finetuned-3d-sentiment

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7236
- Accuracy: 0.7476
- Precision: 0.7515
- Recall: 0.7476
- F1: 0.7474

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.7918        | 1.0   | 1595  | 0.7835          | 0.6718   | 0.6877    | 0.6718 | 0.6697 |
| 0.6103        | 2.0   | 3190  | 0.7777          | 0.6923   | 0.7151    | 0.6923 | 0.6917 |
| 0.5534        | 3.0   | 4785  | 0.6858          | 0.7132   | 0.7250    | 0.7132 | 0.7108 |
| 0.4998        | 4.0   | 6380  | 0.6715          | 0.7333   | 0.7398    | 0.7333 | 0.7325 |
| 0.4327        | 5.0   | 7975  | 0.6745          | 0.7421   | 0.7463    | 0.7421 | 0.7420 |
| 0.3534        | 6.0   | 9570  | 0.7236          | 0.7476   | 0.7515    | 0.7476 | 0.7474 |
| 0.2926        | 7.0   | 11165 | 0.7916          | 0.7456   | 0.7510    | 0.7456 | 0.7457 |


### Framework versions

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