File size: 3,255 Bytes
ff5062f |
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 |
---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: datos-ner
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. -->
# datos-ner
This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0751
- Precision: 0.9516
- Recall: 0.9219
- F1: 0.9365
- Accuracy: 0.9805
## 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
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 38 | 0.6419 | 0.8947 | 0.2656 | 0.4096 | 0.8357 |
| No log | 2.0 | 76 | 0.2665 | 0.8511 | 0.625 | 0.7207 | 0.9276 |
| No log | 3.0 | 114 | 0.1322 | 0.9508 | 0.9062 | 0.9280 | 0.9749 |
| No log | 4.0 | 152 | 0.0907 | 0.9524 | 0.9375 | 0.9449 | 0.9805 |
| No log | 5.0 | 190 | 0.0760 | 0.9683 | 0.9531 | 0.9606 | 0.9833 |
| No log | 6.0 | 228 | 0.0644 | 0.9531 | 0.9531 | 0.9531 | 0.9861 |
| No log | 7.0 | 266 | 0.0728 | 0.9365 | 0.9219 | 0.9291 | 0.9805 |
| No log | 8.0 | 304 | 0.0690 | 0.9365 | 0.9219 | 0.9291 | 0.9805 |
| No log | 9.0 | 342 | 0.0709 | 0.9365 | 0.9219 | 0.9291 | 0.9805 |
| No log | 10.0 | 380 | 0.0781 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| No log | 11.0 | 418 | 0.0654 | 0.9365 | 0.9219 | 0.9291 | 0.9805 |
| No log | 12.0 | 456 | 0.0746 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| No log | 13.0 | 494 | 0.0721 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 14.0 | 532 | 0.0739 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 15.0 | 570 | 0.0765 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 16.0 | 608 | 0.0777 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 17.0 | 646 | 0.0756 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 18.0 | 684 | 0.0765 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 19.0 | 722 | 0.0758 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
| 0.1874 | 20.0 | 760 | 0.0751 | 0.9516 | 0.9219 | 0.9365 | 0.9805 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
|