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---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cardiffnlp_twitter_roberta_base_sentiment_latest_Nov2023
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. -->
# cardiffnlp_twitter_roberta_base_sentiment_latest_Nov2023
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3189
- Accuracy: 0.805
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6619 | 0.2 | 100 | 0.5226 | 0.6285 |
| 0.4526 | 0.4 | 200 | 0.4150 | 0.716 |
| 0.4092 | 0.6 | 300 | 0.3898 | 0.728 |
| 0.3886 | 0.8 | 400 | 0.3441 | 0.773 |
| 0.3822 | 1.0 | 500 | 0.3494 | 0.767 |
| 0.3396 | 1.2 | 600 | 0.3470 | 0.7865 |
| 0.3156 | 1.4 | 700 | 0.3418 | 0.7875 |
| 0.3099 | 1.6 | 800 | 0.3231 | 0.794 |
| 0.2994 | 1.8 | 900 | 0.3371 | 0.7885 |
| 0.2907 | 2.0 | 1000 | 0.3189 | 0.805 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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