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---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
model-index:
- name: finetuned__bert-base-spanish-wwm-cased__augmented-ultrasounds
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__bert-base-spanish-wwm-cased__augmented-ultrasounds
This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5757
## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log | 0.9979 | 238 | 1.0145 |
| 1.2754 | 2.0 | 477 | 0.8811 |
| 1.2754 | 2.9979 | 715 | 0.7855 |
| 0.8342 | 4.0 | 954 | 0.7440 |
| 0.8342 | 4.9979 | 1192 | 0.7016 |
| 0.7436 | 6.0 | 1431 | 0.6743 |
| 0.7436 | 6.9979 | 1669 | 0.6591 |
| 0.6965 | 8.0 | 1908 | 0.6459 |
| 0.6965 | 8.9979 | 2146 | 0.6354 |
| 0.6619 | 10.0 | 2385 | 0.6243 |
| 0.6619 | 10.9979 | 2623 | 0.6177 |
| 0.6386 | 12.0 | 2862 | 0.6086 |
| 0.6386 | 12.9979 | 3100 | 0.6027 |
| 0.623 | 14.0 | 3339 | 0.5828 |
| 0.623 | 14.9979 | 3577 | 0.5869 |
| 0.6103 | 16.0 | 3816 | 0.5951 |
| 0.6103 | 16.9979 | 4054 | 0.5889 |
| 0.6032 | 18.0 | 4293 | 0.5870 |
| 0.6032 | 18.9979 | 4531 | 0.5818 |
| 0.5967 | 19.9581 | 4760 | 0.5757 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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