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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: resume
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. -->
# resume
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0166
- F1: 1.0
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0448 | 1.0 | 49 | 2.7245 | 0.1290 |
| 2.2276 | 2.0 | 98 | 1.7165 | 0.4683 |
| 1.116 | 3.0 | 147 | 0.8720 | 0.8333 |
| 0.5606 | 4.0 | 196 | 0.3686 | 1.0 |
| 0.2374 | 5.0 | 245 | 0.1431 | 1.0 |
| 0.1084 | 6.0 | 294 | 0.0612 | 1.0 |
| 0.0598 | 7.0 | 343 | 0.0328 | 1.0 |
| 0.0386 | 8.0 | 392 | 0.0216 | 1.0 |
| 0.0276 | 9.0 | 441 | 0.0175 | 1.0 |
| 0.0271 | 10.0 | 490 | 0.0166 | 1.0 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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