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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Finetuned-Roberta-Base-Sentiment-identifier
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-Roberta-Base-Sentiment-identifier
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7332
- F1: 0.6622
## 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: 5e-05
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8545 | 0.5 | 500 | 0.8251 | 0.6428 |
| 0.7952 | 1.0 | 1000 | 0.7831 | 0.6445 |
| 0.7962 | 1.5 | 1500 | 0.7935 | 0.6495 |
| 0.7669 | 2.01 | 2000 | 0.7544 | 0.6520 |
| 0.7468 | 2.51 | 2500 | 0.7614 | 0.6724 |
| 0.76 | 3.01 | 3000 | 0.7332 | 0.6622 |
| 0.7352 | 3.51 | 3500 | 0.8651 | 0.6036 |
| 0.7454 | 4.01 | 4000 | 0.7420 | 0.6584 |
| 0.7302 | 4.51 | 4500 | 0.7652 | 0.6573 |
| 0.7099 | 5.02 | 5000 | 0.7372 | 0.6697 |
| 0.73 | 5.52 | 5500 | 0.7806 | 0.6654 |
| 0.7265 | 6.02 | 6000 | 0.7476 | 0.6656 |
| 0.7092 | 6.52 | 6500 | 0.7632 | 0.6535 |
| 0.7322 | 7.02 | 7000 | 0.8017 | 0.6126 |
| 0.7168 | 7.52 | 7500 | 0.8046 | 0.6711 |
| 0.7279 | 8.02 | 8000 | 0.7734 | 0.6652 |
| 0.6884 | 8.53 | 8500 | 0.7806 | 0.6662 |
| 0.6942 | 9.03 | 9000 | 0.7790 | 0.6670 |
| 0.6865 | 9.53 | 9500 | 0.7835 | 0.6650 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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