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---
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
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