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End of training
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---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: RoBERTa-large-GD1-v1
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. -->
# RoBERTa-large-GD1-v1
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7605
- Accuracy: 0.714
- F1: 0.7875
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.631 | 1.0 | 1502 | 0.5333 | 0.766 | 0.8264 |
| 0.5734 | 2.0 | 3004 | 0.5500 | 0.752 | 0.8195 |
| 0.5938 | 3.0 | 4506 | 0.7605 | 0.714 | 0.7875 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3