---
base_model: keefezowie/my_awesome_model
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: my_awesome_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: test
      args: split
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8295
---

<!-- 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. -->

# my_awesome_model

This model is a fine-tuned version of [keefezowie/my_awesome_model](https://huggingface.co/keefezowie/my_awesome_model) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7587
- Accuracy: 0.8295

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3711        | 1.0   | 1000  | 1.1335          | 0.5795   |
| 0.7516        | 2.0   | 2000  | 0.6239          | 0.8065   |
| 0.5061        | 3.0   | 3000  | 0.5523          | 0.823    |
| 0.4381        | 4.0   | 4000  | 0.5857          | 0.8245   |
| 0.3637        | 5.0   | 5000  | 0.5661          | 0.839    |
| 0.3287        | 6.0   | 6000  | 0.5662          | 0.839    |
| 0.296         | 7.0   | 7000  | 0.6437          | 0.835    |
| 0.26          | 8.0   | 8000  | 0.6875          | 0.831    |
| 0.2344        | 9.0   | 9000  | 0.7239          | 0.8255   |
| 0.1989        | 10.0  | 10000 | 0.7587          | 0.8295   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1