File size: 2,977 Bytes
c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de c8209e7 f3ad9de |
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 |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-multilingual-cased
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: multilabel_lora_distilbert_classifier_tuned_ru
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. -->
# multilabel_lora_distilbert_classifier_tuned_ru
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3658
- Accuracy: 0.7845
- F1: 0.7857
- Precision: 0.7997
- Recall: 0.7845
## 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: 4.993596574084884e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0622 | 1.0 | 727 | 0.9090 | 0.6025 | 0.5923 | 0.6149 | 0.6025 |
| 0.9449 | 2.0 | 1454 | 0.7451 | 0.6891 | 0.6855 | 0.6950 | 0.6891 |
| 0.7018 | 3.0 | 2181 | 0.6176 | 0.7359 | 0.7354 | 0.7377 | 0.7359 |
| 0.6192 | 4.0 | 2908 | 0.5854 | 0.7758 | 0.7751 | 0.7805 | 0.7758 |
| 0.4921 | 5.0 | 3635 | 0.5727 | 0.8061 | 0.8050 | 0.8202 | 0.8061 |
| 0.4091 | 6.0 | 4362 | 0.5019 | 0.8294 | 0.8293 | 0.8301 | 0.8294 |
| 0.3273 | 7.0 | 5089 | 0.4864 | 0.8404 | 0.8403 | 0.8409 | 0.8404 |
| 0.3473 | 8.0 | 5816 | 0.4828 | 0.8514 | 0.8512 | 0.8557 | 0.8514 |
| 0.2821 | 9.0 | 6543 | 0.4679 | 0.8597 | 0.8597 | 0.8597 | 0.8597 |
| 0.2599 | 10.0 | 7270 | 0.4874 | 0.8803 | 0.8799 | 0.8823 | 0.8803 |
| 0.2717 | 11.0 | 7997 | 0.4551 | 0.8831 | 0.8829 | 0.8832 | 0.8831 |
| 0.2211 | 12.0 | 8724 | 0.4602 | 0.8858 | 0.8856 | 0.8859 | 0.8858 |
| 0.2207 | 13.0 | 9451 | 0.5086 | 0.8845 | 0.8837 | 0.8862 | 0.8845 |
| 0.2166 | 14.0 | 10178 | 0.4795 | 0.8941 | 0.8936 | 0.8952 | 0.8941 |
| 0.1782 | 15.0 | 10905 | 0.4650 | 0.8955 | 0.8951 | 0.8959 | 0.8955 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1 |