---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finrobberta
  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. -->

# finrobberta

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4613
- Accuracy: 0.84

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8156        | 1.0   | 52   | 0.8772          | 0.5      |
| 0.5711        | 2.0   | 104  | 0.7082          | 0.67     |
| 0.4828        | 3.0   | 156  | 0.5083          | 0.79     |
| 0.3927        | 4.0   | 208  | 0.4988          | 0.83     |
| 0.3866        | 5.0   | 260  | 0.4750          | 0.82     |
| 0.2902        | 6.0   | 312  | 0.4613          | 0.84     |
| 0.2616        | 7.0   | 364  | 0.4632          | 0.82     |
| 0.2209        | 8.0   | 416  | 0.4728          | 0.82     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1