---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: baseline_nli_bert-large
  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-large

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: 0.9293
- Accuracy: 0.6163
- Precision: 0.6163
- Recall: 0.6163
- F1 Score: 0.6185

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.0447        | 1.0   | 2583  | 0.9867          | 0.4602   | 0.4602    | 0.4602 | 0.4166   |
| 0.9632        | 2.0   | 5166  | 0.9132          | 0.5926   | 0.5926    | 0.5926 | 0.5965   |
| 0.9063        | 3.0   | 7749  | 0.8976          | 0.6076   | 0.6076    | 0.6076 | 0.6116   |
| 0.846         | 4.0   | 10332 | 0.8826          | 0.6218   | 0.6218    | 0.6218 | 0.6212   |
| 0.7975        | 5.0   | 12915 | 0.9189          | 0.6136   | 0.6136    | 0.6136 | 0.6169   |
| 0.7605        | 6.0   | 15498 | 0.9293          | 0.6163   | 0.6163    | 0.6163 | 0.6185   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3