---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- precision
- recall
base_model: google/electra-small-discriminator
model-index:
- name: electra-5-epoch-sentiment
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      config: sentiment
      split: test
      args: sentiment
    metrics:
    - type: accuracy
      value: 0.6893520026050146
      name: Accuracy
    - type: precision
      value: 0.6913776305729754
      name: Precision
    - type: recall
      value: 0.6893520026050146
      name: Recall
---

<!-- 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. -->

TOKENIZER & TRAINER CORRUPTED 

# electra-5-epoch-sentiment

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7949
- Accuracy: 0.6894
- Precision: 0.6914
- Recall: 0.6894
- Micro-avg-recall: 0.6894
- Micro-avg-precision: 0.6894

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
| 0.5949        | 1.0   | 2851  | 0.6963          | 0.6926   | 0.6943    | 0.6926 | 0.6926           | 0.6926              |
| 0.6502        | 2.0   | 5702  | 0.7348          | 0.6911   | 0.6929    | 0.6911 | 0.6911           | 0.6911              |
| 0.556         | 3.0   | 8553  | 0.7322          | 0.6943   | 0.6952    | 0.6943 | 0.6943           | 0.6943              |
| 0.4561        | 4.0   | 11404 | 0.7601          | 0.6895   | 0.6916    | 0.6895 | 0.6895           | 0.6895              |
| 0.471         | 5.0   | 14255 | 0.7949          | 0.6894   | 0.6914    | 0.6894 | 0.6894           | 0.6894              |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3