---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: all
      split: validation
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6361882716049383
    - name: F1
      type: f1
      value: 0.6387023843949189
---

<!-- 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. -->

# scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0269
- Accuracy: 0.6362
- F1: 0.6387

## 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: 32
- eval_batch_size: 32
- seed: 66
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8991        | 1.09  | 500  | 0.8258          | 0.6265   | 0.6117 |
| 0.6873        | 2.17  | 1000 | 0.8627          | 0.6481   | 0.6502 |
| 0.5102        | 3.26  | 1500 | 0.9726          | 0.6516   | 0.6440 |
| 0.3825        | 4.35  | 2000 | 1.1881          | 0.6578   | 0.6540 |
| 0.2946        | 5.43  | 2500 | 1.2475          | 0.6532   | 0.6554 |
| 0.228         | 6.52  | 3000 | 1.5294          | 0.6435   | 0.6458 |
| 0.2006        | 7.61  | 3500 | 1.6058          | 0.6389   | 0.6342 |
| 0.159         | 8.7   | 4000 | 1.5956          | 0.6528   | 0.6510 |
| 0.1334        | 9.78  | 4500 | 1.8463          | 0.6478   | 0.6409 |
| 0.1052        | 10.87 | 5000 | 2.0269          | 0.6362   | 0.6387 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3