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

# baseline_nli_bert

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9280
- Accuracy: 0.6063
- Precision: 0.6063
- Recall: 0.6063
- F1 Score: 0.6088

## 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: 3e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 101
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.0366        | 1.0   | 2583  | 0.9579          | 0.5603   | 0.5603    | 0.5603 | 0.5638   |
| 0.9416        | 2.0   | 5166  | 0.9206          | 0.5826   | 0.5826    | 0.5826 | 0.5877   |
| 0.8889        | 3.0   | 7749  | 0.9085          | 0.5981   | 0.5981    | 0.5981 | 0.6025   |
| 0.8539        | 4.0   | 10332 | 0.9176          | 0.6054   | 0.6054    | 0.6054 | 0.6089   |
| 0.8323        | 5.0   | 12915 | 0.9201          | 0.6049   | 0.6049    | 0.6049 | 0.6066   |
| 0.811         | 6.0   | 15498 | 0.9280          | 0.6063   | 0.6063    | 0.6063 | 0.6088   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.12.1
- Datasets 2.11.0
- Tokenizers 0.13.2