transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:liar base_model:google-bert/bert-base-cased base_model:finetune:google-bert/bert-base-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-cased
datasets:
- liar
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: liar_binaryclassifier_bert_cased
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: liar
      type: liar
      config: default
      split: test
      args: default
    metrics:
    - type: accuracy
      value: 0.648590021691974
      name: Accuracy
---

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# liar_binaryclassifier_bert_cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the liar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6331
- Model Preparation Time: 0.0032
- Accuracy: 0.6486

## 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: 8
- eval_batch_size: 8
- 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 | Model Preparation Time | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
| 0.6826        | 1.0   | 461  | 0.6477          | 0.0032                 | 0.6117   |
| 0.6435        | 2.0   | 922  | 0.6267          | 0.0032                 | 0.6356   |
| 0.6131        | 3.0   | 1383 | 0.6302          | 0.0032                 | 0.6529   |
| 0.5809        | 4.0   | 1844 | 0.6233          | 0.0032                 | 0.6508   |
| 0.5658        | 5.0   | 2305 | 0.6331          | 0.0032                 | 0.6486   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
