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---
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: bnb-sentiment-model-saagie
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.9444444444444444
---
<!-- 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. -->
# bnb-sentiment-model-saagie
This model is a fine-tuned version of [j-hartmann/emotion-english-distilroberta-base](https://huggingface.co/j-hartmann/emotion-english-distilroberta-base) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3581
- Accuracy: 0.9444
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3724 | 1.0 | 1875 | 0.1799 | 0.9367 |
| 0.2118 | 2.0 | 3750 | 0.1918 | 0.9456 |
| 0.1792 | 3.0 | 5625 | 0.1791 | 0.95 |
| 0.1489 | 4.0 | 7500 | 0.1479 | 0.9489 |
| 0.1168 | 5.0 | 9375 | 0.2561 | 0.9444 |
| 0.081 | 6.0 | 11250 | 0.2863 | 0.9411 |
| 0.0521 | 7.0 | 13125 | 0.3168 | 0.9467 |
| 0.0345 | 8.0 | 15000 | 0.3581 | 0.9444 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.8.1
- Datasets 2.12.0
- Tokenizers 0.12.1
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