---
library_name: transformers
license: mit
base_model: sergeyzh/BERTA
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: berta_report_classifier
  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. -->

# berta_report_classifier

This model is a fine-tuned version of [sergeyzh/BERTA](https://huggingface.co/sergeyzh/BERTA) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0030
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0286        | 1.0   | 70   | 0.0343          | 0.99     | 0.9900 | 0.9902    | 0.99   |
| 0.0351        | 2.0   | 140  | 0.0030          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0103        | 3.0   | 210  | 0.0077          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0011        | 4.0   | 280  | 0.0008          | 1.0      | 1.0    | 1.0       | 1.0    |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu124
- Datasets 2.14.6
- Tokenizers 0.20.3