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license: apache-2.0
base_model: BSC-LT/roberta-base-bne
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: services-ucacue
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. -->
# services-ucacue
This model is a fine-tuned version of [BSC-LT/roberta-base-bne](https://huggingface.co/BSC-LT/roberta-base-bne) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5312
- Accuracy: 0.8260
## 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: 40
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3007 | 1.0 | 158 | 0.6027 | 0.7798 |
| 0.5036 | 2.0 | 316 | 0.4827 | 0.8213 |
| 0.3994 | 3.0 | 474 | 0.4975 | 0.8213 |
| 0.2731 | 4.0 | 632 | 0.4928 | 0.8181 |
| 0.2132 | 5.0 | 790 | 0.5312 | 0.8260 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|