---
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