README.md

---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: norbert2_sentiment_norec_13
  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. -->

# norbert2_sentiment_norec_13

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6303
- Compute Metrics: :
- Accuracy: 0.6
- Balanced Accuracy: 0.375
- F1 Score: 0.75
- Recall: 0.75
- Precision: 0.75

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Compute Metrics | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:--------:|:-----------------:|:--------:|:------:|:---------:|
| 0.6492        | 1.0   | 3    | 0.6466          | :               | 0.6      | 0.375             | 0.75     | 0.75   | 0.75      |
| 0.3086        | 2.0   | 6    | 0.6303          | :               | 0.6      | 0.375             | 0.75     | 0.75   | 0.75      |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2