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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-base-cased
model-index:
- name: finetuned-Sentiment-classfication-BERT-model
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. -->
# finetuned-Sentiment-classfication-BERT-model
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6056
- Rmse: 0.6890
## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7754 | 2.0 | 500 | 0.6056 | 0.6890 |
| 0.3975 | 4.0 | 1000 | 0.6982 | 0.6452 |
| 0.1308 | 6.0 | 1500 | 1.0715 | 0.6643 |
| 0.0526 | 8.0 | 2000 | 1.3439 | 0.6571 |
| 0.0241 | 10.0 | 2500 | 1.4676 | 0.6695 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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