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---
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
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