---
library_name: transformers
language:
- en
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-base-tweet-sentiment
  results: []
---

<!-- 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. -->

# deberta-base-tweet-sentiment

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the Twitter Sentiment Datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4842
- Accuracy: 0.8019

## 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: 1.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8569        | 0.9985 | 332  | 0.5507          | 0.7729   |
| 0.5439        | 2.0    | 665  | 0.5021          | 0.7947   |
| 0.4502        | 2.9985 | 997  | 0.4842          | 0.8019   |
| 0.3801        | 4.0    | 1330 | 0.5064          | 0.8013   |
| 0.3387        | 4.9925 | 1660 | 0.5141          | 0.8057   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1