File size: 2,320 Bytes
c006c62 5153cac c006c62 5153cac c006c62 5153cac c006c62 5153cac c006c62 5153cac c006c62 5153cac c006c62 80a7921 5153cac c006c62 |
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 87 88 89 90 91 92 93 94 |
---
license: cc-by-nc-sa-4.0
base_model: ufal/robeczech-base
tags:
- generated_from_trainer
datasets:
- cnec
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CNEC_1_1_robeczech-base
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cnec
type: cnec
config: default
split: validation
args: default
metrics:
- name: Precision
type: precision
value: 0.8540680154972019
- name: Recall
type: recall
value: 0.8759381898454747
- name: F1
type: f1
value: 0.8648648648648649
- name: Accuracy
type: accuracy
value: 0.9496757457846952
---
<!-- 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. -->
# CNEC_1_1_robeczech-base
This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co./ufal/robeczech-base) on the cnec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2682
- Precision: 0.8541
- Recall: 0.8759
- F1: 0.8649
- Accuracy: 0.9497
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5187 | 6.8 | 1000 | 0.3863 | 0.7882 | 0.8115 | 0.7997 | 0.9328 |
| 0.222 | 13.61 | 2000 | 0.2829 | 0.8376 | 0.8561 | 0.8467 | 0.9463 |
| 0.1408 | 20.41 | 3000 | 0.2662 | 0.8493 | 0.8684 | 0.8588 | 0.9493 |
| 0.1071 | 27.21 | 4000 | 0.2682 | 0.8541 | 0.8759 | 0.8649 | 0.9497 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|