---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: feedback-classification
  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. -->

# feedback-classification

This model is a fine-tuned version of [qarib/bert-base-qarib_far_9920k](https://huggingface.co/qarib/bert-base-qarib_far_9920k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0442
- Macro F1: 0.8311
- Accuracy: 0.8275

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 | Macro F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   | 342  | 0.5528          | 0.7897   | 0.7851   |
| 0.5472        | 2.0   | 684  | 0.6922          | 0.8200   | 0.8129   |
| 0.2753        | 3.0   | 1026 | 0.9658          | 0.8113   | 0.8070   |
| 0.2753        | 4.0   | 1368 | 0.9768          | 0.8349   | 0.8304   |
| 0.1171        | 5.0   | 1710 | 1.0442          | 0.8311   | 0.8275   |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3