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---
library_name: peft
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_model
results: []
license: apache-2.0
datasets:
- mteb/amazon_reviews_multi
language:
- en
---
<!-- 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. -->
# fine_tuned_model
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on [mteb/amazon_reviews_multi](https://huggingface.co/datasets/mteb/amazon_reviews_multi).
It achieves the following results on the evaluation set:
- Loss: 0.4604
- Accuracy: 0.81
- F1 Macro: 0.7564
- Precision Macro: 0.7654
- Recall Macro: 0.7533
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 0.5451 | 1.0 | 5000 | 0.5156 | 0.783 | 0.7111 | 0.7280 | 0.7110 |
| 0.4961 | 2.0 | 10000 | 0.4619 | 0.809 | 0.7591 | 0.7647 | 0.7567 |
| 0.498 | 3.0 | 15000 | 0.4604 | 0.81 | 0.7564 | 0.7654 | 0.7533 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0 |