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tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: sentiment-roberta_base-e4-b16
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. -->
# sentiment-roberta_base-e4-b16
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6110
- F1: 0.7385
- Recall: 0.7385
- Precision: 0.7385
## 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| No log | 1.0 | 375 | 0.8888 | 0.7493 | 0.7493 | 0.7493 |
| 0.461 | 2.0 | 750 | 1.1518 | 0.7493 | 0.7493 | 0.7493 |
| 0.1578 | 3.0 | 1125 | 1.5342 | 0.7358 | 0.7358 | 0.7358 |
| 0.0658 | 4.0 | 1500 | 1.6110 | 0.7385 | 0.7385 | 0.7385 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|