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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DistilBERT-finetuned-on-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.9235
- name: F1
type: f1
value: 0.9234955371382243
widget:
- text: >-
The gentle touch of your hand on mine is a silent promise that echoes
through the corridors of my heart.
- text: ' Walking through the dusty attic, I stumbled upon a hidden door. With a mix of trepidation and excitement, I pushed it open, expecting cobwebs and forgotten junk. Instead, a flood of sunlight revealed a secret garden, blooming with vibrant flowers and buzzing with life. My jaw dropped in pure astonishment.'
- text: >-
The rain mirrored the tears I couldn't stop, each drop a tiny echo of the
ache in my heart. The world seemed muted, colors drained, and a heavy weight
settled upon my soul.
- text: >-
Staring at your pic, smiling. It feels like I am living this night awake in
ur dreams. I went through our chats all of them n each word kissed my heart
with gratitude. Suddenly, I felt like I am choking. my eyes welling up .my
breath turned warm n deep n I even felt some chill on my skin.
language:
- en
---
<!-- 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. -->
# DistilBERT-finetuned-on-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2180
- Accuracy: 0.9235
- F1: 0.9235
## Model description
DiestilBERT is fine-tuned on emotions dataset. Click the following link to see how the model works:
https://huggingface.co./spaces/Rahmat82/emotions_classifier
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8046 | 1.0 | 250 | 0.3115 | 0.9085 | 0.9081 |
| 0.2405 | 2.0 | 500 | 0.2180 | 0.9235 | 0.9235 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0 |