transformers pytorch tensorboard roberta token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: DisTEMIST_fine_tuned_sentence
  results: []
---

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# DisTEMIST_fine_tuned_sentence

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2164
- Precision: 0.6069
- Recall: 0.6401
- F1: 0.6231

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=2.6e-09
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 73
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
| 0.1166        | 1.0   | 1099  | 0.1152          | 0.5214    | 0.6433 | 0.5760 |
| 0.0718        | 2.0   | 2198  | 0.1096          | 0.6015    | 0.6297 | 0.6153 |
| 0.0438        | 3.0   | 3297  | 0.1517          | 0.6573    | 0.5895 | 0.6215 |
| 0.0293        | 4.0   | 4396  | 0.1496          | 0.6212    | 0.6198 | 0.6205 |
| 0.0179        | 5.0   | 5495  | 0.1665          | 0.5670    | 0.6505 | 0.6059 |
| 0.0119        | 6.0   | 6594  | 0.1602          | 0.6035    | 0.6379 | 0.6202 |
| 0.0078        | 7.0   | 7693  | 0.1844          | 0.6008    | 0.6347 | 0.6173 |
| 0.0041        | 8.0   | 8792  | 0.2019          | 0.6006    | 0.6288 | 0.6144 |
| 0.0026        | 9.0   | 9891  | 0.2075          | 0.6015    | 0.6270 | 0.6140 |
| 0.0014        | 10.0  | 10990 | 0.2164          | 0.6069    | 0.6401 | 0.6231 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
