File size: 2,028 Bytes
15d3d5b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
- precision
model-index:
- name: roberta-base-fine-tuned-text-classificarion-ds-ss3
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. -->
# roberta-base-fine-tuned-text-classificarion-ds-ss3
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0250
- F1: 0.7788
- Recall: 0.7819
- Accuracy: 0.7819
- Precision: 0.7902
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
| No log | 1.0 | 442 | 1.4320 | 0.6547 | 0.6927 | 0.6927 | 0.6529 |
| 2.1286 | 2.0 | 884 | 1.1279 | 0.7089 | 0.7386 | 0.7386 | 0.7006 |
| 1.0149 | 3.0 | 1326 | 1.0204 | 0.7350 | 0.7513 | 0.7513 | 0.7355 |
| 0.6117 | 4.0 | 1768 | 0.9823 | 0.7552 | 0.7698 | 0.7698 | 0.7724 |
| 0.3659 | 5.0 | 2210 | 1.0250 | 0.7788 | 0.7819 | 0.7819 | 0.7902 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|