---
base_model: dianamihalache27/Twroberta-baseB_5epoch
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ceva
  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. -->

# ceva

This model is a fine-tuned version of [dianamihalache27/Twroberta-baseB_5epoch](https://huggingface.co/dianamihalache27/Twroberta-baseB_5epoch) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1932
- Accuracy: 0.7714
- F1: 0.2892
- Precision: 0.2435
- Recall: 0.3579
- Precision Sarcastic: 0.3372
- Recall Sarcastic: 0.4833
- F1 Sarcastic: 0.3973

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 217  | 0.1618          | 0.7893   | 0.2947 | 0.2611    | 0.3395 | 0.3458              | 0.4611           | 0.3952       |
| No log        | 2.0   | 434  | 0.1815          | 0.7629   | 0.3104 | 0.2560    | 0.4059 | 0.3299              | 0.5278           | 0.4060       |
| 0.0559        | 3.0   | 651  | 0.1762          | 0.8      | 0.2957 | 0.2991    | 0.3173 | 0.3721              | 0.4444           | 0.4051       |
| 0.0559        | 4.0   | 868  | 0.1811          | 0.7636   | 0.2933 | 0.2418    | 0.3727 | 0.3297              | 0.5111           | 0.4009       |
| 0.0245        | 5.0   | 1085 | 0.1932          | 0.7714   | 0.2892 | 0.2435    | 0.3579 | 0.3372              | 0.4833           | 0.3973       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1