---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: google/electra-base-discriminator
model-index:
- name: electra-base-discriminator-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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# electra-base-discriminator-finetuned-3d-sentiment

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5887
- Accuracy: 0.7873
- Precision: 0.7897
- Recall: 0.7873
- F1: 0.7864

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.797         | 1.0   | 1595  | 0.7075          | 0.7353   | 0.7434    | 0.7353 | 0.7357 |
| 0.5329        | 2.0   | 3190  | 0.6508          | 0.7550   | 0.7646    | 0.7550 | 0.7554 |
| 0.4597        | 3.0   | 4785  | 0.5889          | 0.7702   | 0.7803    | 0.7702 | 0.7695 |
| 0.3918        | 4.0   | 6380  | 0.5887          | 0.7873   | 0.7897    | 0.7873 | 0.7864 |
| 0.3093        | 5.0   | 7975  | 0.6412          | 0.7833   | 0.7877    | 0.7833 | 0.7836 |
| 0.2144        | 6.0   | 9570  | 0.7786          | 0.7844   | 0.7900    | 0.7844 | 0.7851 |
| 0.1507        | 7.0   | 11165 | 0.8455          | 0.7853   | 0.7903    | 0.7853 | 0.7862 |


### Framework versions

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