---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-base-uncased-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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# bert-base-uncased-finetuned-3d-sentiment

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9271
- Accuracy: 0.7392
- Precision: 0.7455
- Recall: 0.7392
- F1: 0.7394

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8443        | 1.0   | 1595  | 0.8265          | 0.6659   | 0.6920    | 0.6659 | 0.6629 |
| 0.6037        | 2.0   | 3190  | 0.7380          | 0.7021   | 0.7207    | 0.7021 | 0.7014 |
| 0.516         | 3.0   | 4785  | 0.6740          | 0.7246   | 0.7337    | 0.7246 | 0.7234 |
| 0.4269        | 4.0   | 6380  | 0.7221          | 0.7290   | 0.7383    | 0.7290 | 0.7271 |
| 0.3149        | 5.0   | 7975  | 0.8368          | 0.7237   | 0.7422    | 0.7237 | 0.7230 |
| 0.1996        | 6.0   | 9570  | 0.9271          | 0.7392   | 0.7455    | 0.7392 | 0.7394 |
| 0.1299        | 7.0   | 11165 | 1.1062          | 0.7358   | 0.7461    | 0.7358 | 0.7361 |


### Framework versions

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