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---
license: mit
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
model-index:
- name: emotion_classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
config: simplified
split: validation
args: simplified
metrics:
- name: F1
type: f1
value: 0.38517334250011687
---
<!-- 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. -->
# emotion_classification
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6119
- F1: 0.3852
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 313 | 1.8826 | 0.1762 |
| 2.1614 | 2.0 | 626 | 1.6738 | 0.3442 |
| 2.1614 | 3.0 | 939 | 1.6119 | 0.3852 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|