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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
model-index:
- name: ft-bert-base-uncased-for-sentiment-classification
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. -->
# ft-bert-base-uncased-for-sentiment-classification
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the https://huggingface.co./datasets/takala/financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1120
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1649 | 1.0 | 128 | 0.1319 |
| 0.1322 | 2.0 | 256 | 0.1232 |
| 0.0092 | 3.0 | 384 | 0.1120 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|