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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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