update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- precision
|
| 7 |
+
- recall
|
| 8 |
+
- f1
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: prueba4
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
+
|
| 18 |
+
# prueba4
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.2044
|
| 23 |
+
- Precision: 0.7288
|
| 24 |
+
- Recall: 0.6853
|
| 25 |
+
- F1: 0.7064
|
| 26 |
+
- Accuracy: 0.9752
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 2.75e-05
|
| 46 |
+
- train_batch_size: 16
|
| 47 |
+
- eval_batch_size: 8
|
| 48 |
+
- seed: 42
|
| 49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 15
|
| 52 |
+
|
| 53 |
+
### Training results
|
| 54 |
+
|
| 55 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 56 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 57 |
+
| No log | 1.0 | 57 | 0.2361 | 0.6504 | 0.6892 | 0.6692 | 0.9694 |
|
| 58 |
+
| No log | 2.0 | 114 | 0.2441 | 0.6190 | 0.6733 | 0.6450 | 0.9671 |
|
| 59 |
+
| No log | 3.0 | 171 | 0.2064 | 0.6013 | 0.7211 | 0.6558 | 0.9699 |
|
| 60 |
+
| No log | 4.0 | 228 | 0.2241 | 0.7004 | 0.6335 | 0.6653 | 0.9720 |
|
| 61 |
+
| No log | 5.0 | 285 | 0.1992 | 0.6578 | 0.6892 | 0.6732 | 0.9727 |
|
| 62 |
+
| No log | 6.0 | 342 | 0.2149 | 0.6073 | 0.7331 | 0.6643 | 0.9694 |
|
| 63 |
+
| No log | 7.0 | 399 | 0.2099 | 0.7466 | 0.6574 | 0.6992 | 0.9755 |
|
| 64 |
+
| No log | 8.0 | 456 | 0.2039 | 0.7293 | 0.6653 | 0.6958 | 0.9747 |
|
| 65 |
+
| 0.0017 | 9.0 | 513 | 0.2185 | 0.7342 | 0.6494 | 0.6892 | 0.9742 |
|
| 66 |
+
| 0.0017 | 10.0 | 570 | 0.2074 | 0.688 | 0.6853 | 0.6866 | 0.9732 |
|
| 67 |
+
| 0.0017 | 11.0 | 627 | 0.2010 | 0.7073 | 0.6932 | 0.7002 | 0.9745 |
|
| 68 |
+
| 0.0017 | 12.0 | 684 | 0.2030 | 0.7126 | 0.7012 | 0.7068 | 0.9749 |
|
| 69 |
+
| 0.0017 | 13.0 | 741 | 0.2045 | 0.7173 | 0.6773 | 0.6967 | 0.9745 |
|
| 70 |
+
| 0.0017 | 14.0 | 798 | 0.2040 | 0.7185 | 0.6813 | 0.6994 | 0.9747 |
|
| 71 |
+
| 0.0017 | 15.0 | 855 | 0.2044 | 0.7288 | 0.6853 | 0.7064 | 0.9752 |
|
| 72 |
+
|
| 73 |
+
|
| 74 |
+
### Framework versions
|
| 75 |
+
|
| 76 |
+
- Transformers 4.27.3
|
| 77 |
+
- Pytorch 1.13.1+cu116
|
| 78 |
+
- Datasets 2.10.1
|
| 79 |
+
- Tokenizers 0.13.2
|