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Librarian Bot: Add base_model information to model (#2)
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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
base_model: nlptown/bert-base-multilingual-uncased-sentiment
model-index:
- name: bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos
results: []
---
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# bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos
This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9409
- F1: 0.5890
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.9601 | 1.0 | 383 | 0.9355 | 0.5774 |
| 0.8103 | 2.0 | 766 | 0.9409 | 0.5890 |
### Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1+cu116
- Datasets 2.13.1
- Tokenizers 0.12.1