---
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finetuning-sentiment-model-youtube-samples
  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. -->

# finetuning-sentiment-model-youtube-samples

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: 0.9901
- Accuracy: 0.8418
- F1: 0.8381
- Precision: 0.8418
- Recall: 0.8418

## 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: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6387        | 1.0   | 22   | 0.6277          | 0.7062   | 0.7069 | 0.7062    | 0.7062 |
| 0.3508        | 2.0   | 44   | 0.4970          | 0.8023   | 0.8043 | 0.8023    | 0.8023 |
| 0.1586        | 3.0   | 66   | 0.8574          | 0.7910   | 0.7829 | 0.7910    | 0.7910 |
| 0.0663        | 4.0   | 88   | 0.7822          | 0.8079   | 0.8086 | 0.8079    | 0.8079 |
| 0.0351        | 5.0   | 110  | 0.8371          | 0.8305   | 0.8188 | 0.8305    | 0.8305 |
| 0.0274        | 6.0   | 132  | 0.8634          | 0.8475   | 0.8423 | 0.8475    | 0.8475 |
| 0.0049        | 7.0   | 154  | 0.9682          | 0.8079   | 0.8023 | 0.8079    | 0.8079 |
| 0.0015        | 8.0   | 176  | 0.9604          | 0.8362   | 0.8348 | 0.8362    | 0.8362 |
| 0.0007        | 9.0   | 198  | 0.9754          | 0.8418   | 0.8381 | 0.8418    | 0.8418 |
| 0.0011        | 10.0  | 220  | 0.9901          | 0.8418   | 0.8381 | 0.8418    | 0.8418 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3