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---
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
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