---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: sentic-singletTextWcBerta-Fold1
  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. -->

# sentic-singletTextWcBerta-Fold1

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5627
- Accuracy: 0.7510
- Precision: 0.7401
- Recall: 0.7510
- F1 Score: 0.7431

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log        | 1.0   | 60   | 0.6901          | 0.7040   | 0.7917    | 0.7040 | 0.5827   |
| 0.501         | 2.0   | 120  | 0.5192          | 0.7354   | 0.7138    | 0.7354 | 0.6994   |
| 0.501         | 3.0   | 180  | 0.5411          | 0.7270   | 0.7045    | 0.7270 | 0.7048   |
| 0.4839        | 4.0   | 240  | 0.8009          | 0.7029   | 0.6429    | 0.7029 | 0.5822   |
| 0.4849        | 5.0   | 300  | 0.5294          | 0.7374   | 0.7163    | 0.7374 | 0.7066   |
| 0.4849        | 6.0   | 360  | 0.5430          | 0.7301   | 0.7109    | 0.7301 | 0.7132   |
| 0.4684        | 7.0   | 420  | 0.5570          | 0.7312   | 0.7104    | 0.7312 | 0.7110   |
| 0.4684        | 8.0   | 480  | 0.5740          | 0.7416   | 0.7258    | 0.7416 | 0.7006   |
| 0.4182        | 9.0   | 540  | 0.6109          | 0.7458   | 0.7328    | 0.7458 | 0.7054   |
| 0.4052        | 10.0  | 600  | 0.5607          | 0.7490   | 0.7357    | 0.7490 | 0.7383   |
| 0.4052        | 11.0  | 660  | 0.5974          | 0.7510   | 0.7369    | 0.7510 | 0.7182   |
| 0.3884        | 12.0  | 720  | 0.5715          | 0.7333   | 0.7423    | 0.7333 | 0.7370   |
| 0.3884        | 13.0  | 780  | 0.5603          | 0.7552   | 0.7463    | 0.7552 | 0.7492   |
| 0.364         | 14.0  | 840  | 0.5610          | 0.7573   | 0.7511    | 0.7573 | 0.7535   |
| 0.3564        | 15.0  | 900  | 0.5627          | 0.7510   | 0.7401    | 0.7510 | 0.7431   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1