File size: 3,350 Bytes
e3f12cc eb4dc9d e3f12cc 838eb89 e3f12cc eb4dc9d e3f12cc 838eb89 e3f12cc 838eb89 e3f12cc 838eb89 eb4dc9d e3f12cc |
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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
---
license: cc-by-4.0
base_model: bertin-project/bertin-roberta-base-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-model-Bertin-Area
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. -->
# my-model-Bertin-Area
This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1711
- Accuracy: 0.4903
- F1: 0.4767
- Precision: 0.5366
- Recall: 0.4903
## 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: 30
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.8349 | 1.0 | 25 | 1.7703 | 0.3032 | 0.2608 | 0.2991 | 0.3032 |
| 1.7709 | 2.0 | 50 | 1.7153 | 0.3355 | 0.2347 | 0.2079 | 0.3355 |
| 1.7315 | 3.0 | 75 | 1.6515 | 0.3613 | 0.2934 | 0.2937 | 0.3613 |
| 1.596 | 4.0 | 100 | 1.6332 | 0.3871 | 0.3405 | 0.3123 | 0.3871 |
| 1.3388 | 5.0 | 125 | 1.6449 | 0.4065 | 0.3298 | 0.2900 | 0.4065 |
| 1.0783 | 6.0 | 150 | 1.5722 | 0.4581 | 0.3797 | 0.3760 | 0.4581 |
| 0.8663 | 7.0 | 175 | 1.6593 | 0.3935 | 0.3563 | 0.3490 | 0.3935 |
| 0.6118 | 8.0 | 200 | 1.9177 | 0.4581 | 0.4481 | 0.4658 | 0.4581 |
| 0.4206 | 9.0 | 225 | 2.2944 | 0.4065 | 0.3920 | 0.4286 | 0.4065 |
| 0.3375 | 10.0 | 250 | 2.2870 | 0.4387 | 0.4359 | 0.4889 | 0.4387 |
| 0.2334 | 11.0 | 275 | 2.4912 | 0.4065 | 0.4015 | 0.4546 | 0.4065 |
| 0.1618 | 12.0 | 300 | 2.5429 | 0.4710 | 0.4499 | 0.5204 | 0.4710 |
| 0.1238 | 13.0 | 325 | 2.7109 | 0.4710 | 0.4458 | 0.5135 | 0.4710 |
| 0.0906 | 14.0 | 350 | 2.8377 | 0.4774 | 0.4594 | 0.5092 | 0.4774 |
| 0.071 | 15.0 | 375 | 3.0123 | 0.4839 | 0.4656 | 0.5461 | 0.4839 |
| 0.0498 | 16.0 | 400 | 3.0204 | 0.4710 | 0.4517 | 0.4959 | 0.4710 |
| 0.0416 | 17.0 | 425 | 3.0939 | 0.4839 | 0.4622 | 0.5107 | 0.4839 |
| 0.0281 | 18.0 | 450 | 3.0979 | 0.4903 | 0.4793 | 0.5281 | 0.4903 |
| 0.0226 | 19.0 | 475 | 3.1622 | 0.4839 | 0.4708 | 0.5202 | 0.4839 |
| 0.0185 | 20.0 | 500 | 3.1711 | 0.4903 | 0.4767 | 0.5366 | 0.4903 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|