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---
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
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