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library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: test_trainer
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. -->
# test_trainer
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2791
- Accuracy: 0.794
- F1: 0.7938
- Precision: 0.7958
- Recall: 0.7986
## 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: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4814 | 1.0 | 55 | 0.5014 | 0.793 | 0.7925 | 0.7935 | 0.8008 |
| 0.3957 | 2.0 | 110 | 0.5091 | 0.806 | 0.8050 | 0.8120 | 0.8030 |
| 0.2667 | 3.0 | 165 | 0.6027 | 0.815 | 0.8149 | 0.8195 | 0.8148 |
| 0.1823 | 4.0 | 220 | 0.7652 | 0.802 | 0.8015 | 0.8021 | 0.8088 |
| 0.1114 | 5.0 | 275 | 0.8443 | 0.808 | 0.8080 | 0.8105 | 0.8117 |
| 0.0862 | 6.0 | 330 | 0.9307 | 0.802 | 0.8021 | 0.8043 | 0.8072 |
| 0.0422 | 7.0 | 385 | 1.0603 | 0.792 | 0.7919 | 0.7943 | 0.7958 |
| 0.0323 | 8.0 | 440 | 1.1902 | 0.793 | 0.7928 | 0.7948 | 0.7982 |
| 0.0195 | 9.0 | 495 | 1.2363 | 0.791 | 0.7909 | 0.7941 | 0.7941 |
| 0.0172 | 10.0 | 550 | 1.2791 | 0.794 | 0.7938 | 0.7958 | 0.7986 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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