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---
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: BERTicSENTNEG4
  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. -->

# BERTicSENTNEG4

This model is a fine-tuned version of [Tanor/BERTicSENTNEG4](https://huggingface.co/Tanor/BERTicSENTNEG4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0842
- F1: 0.6275

## 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: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 53   | 0.0668          | 0.0    |
| No log        | 2.0   | 106  | 0.0432          | 0.6383 |
| No log        | 3.0   | 159  | 0.0400          | 0.5714 |
| No log        | 4.0   | 212  | 0.0458          | 0.5957 |
| No log        | 5.0   | 265  | 0.0444          | 0.5882 |
| No log        | 6.0   | 318  | 0.0556          | 0.5957 |
| No log        | 7.0   | 371  | 0.0566          | 0.5714 |
| No log        | 8.0   | 424  | 0.0587          | 0.5862 |
| No log        | 9.0   | 477  | 0.0566          | 0.5660 |
| 0.0389        | 10.0  | 530  | 0.0693          | 0.5455 |
| 0.0389        | 11.0  | 583  | 0.0612          | 0.6383 |
| 0.0389        | 12.0  | 636  | 0.0596          | 0.6    |
| 0.0389        | 13.0  | 689  | 0.0671          | 0.6038 |
| 0.0389        | 14.0  | 742  | 0.0740          | 0.5957 |
| 0.0389        | 15.0  | 795  | 0.0799          | 0.5778 |
| 0.0389        | 16.0  | 848  | 0.0702          | 0.5957 |
| 0.0389        | 17.0  | 901  | 0.0737          | 0.6087 |
| 0.0389        | 18.0  | 954  | 0.0674          | 0.5660 |
| 0.0053        | 19.0  | 1007 | 0.0725          | 0.5957 |
| 0.0053        | 20.0  | 1060 | 0.0738          | 0.6    |
| 0.0053        | 21.0  | 1113 | 0.0821          | 0.625  |
| 0.0053        | 22.0  | 1166 | 0.0737          | 0.6    |
| 0.0053        | 23.0  | 1219 | 0.0828          | 0.6122 |
| 0.0053        | 24.0  | 1272 | 0.0776          | 0.6182 |
| 0.0053        | 25.0  | 1325 | 0.0792          | 0.6182 |
| 0.0053        | 26.0  | 1378 | 0.0791          | 0.6275 |
| 0.0053        | 27.0  | 1431 | 0.0812          | 0.6275 |
| 0.0053        | 28.0  | 1484 | 0.0819          | 0.6038 |
| 0.0029        | 29.0  | 1537 | 0.0831          | 0.6275 |
| 0.0029        | 30.0  | 1590 | 0.0834          | 0.6275 |
| 0.0029        | 31.0  | 1643 | 0.0837          | 0.6275 |
| 0.0029        | 32.0  | 1696 | 0.0842          | 0.6275 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.13.3