Commit
•
406f1fa
1
Parent(s):
91a46f3
Training complete
Browse files
README.md
ADDED
|
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: bert-base-multilingual-cased
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
metrics:
|
| 7 |
+
- precision
|
| 8 |
+
- recall
|
| 9 |
+
- f1
|
| 10 |
+
- accuracy
|
| 11 |
+
model-index:
|
| 12 |
+
- name: NLP-HIBA_DisTEMIST_fine_tuned_bert-base-multilingual-cased
|
| 13 |
+
results: []
|
| 14 |
+
---
|
| 15 |
+
|
| 16 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 17 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 18 |
+
|
| 19 |
+
# NLP-HIBA_DisTEMIST_fine_tuned_bert-base-multilingual-cased
|
| 20 |
+
|
| 21 |
+
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
|
| 22 |
+
It achieves the following results on the evaluation set:
|
| 23 |
+
- Loss: 0.2057
|
| 24 |
+
- Precision: 0.6288
|
| 25 |
+
- Recall: 0.5579
|
| 26 |
+
- F1: 0.5912
|
| 27 |
+
- Accuracy: 0.9555
|
| 28 |
+
|
| 29 |
+
## Model description
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Intended uses & limitations
|
| 34 |
+
|
| 35 |
+
More information needed
|
| 36 |
+
|
| 37 |
+
## Training and evaluation data
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Training procedure
|
| 42 |
+
|
| 43 |
+
### Training hyperparameters
|
| 44 |
+
|
| 45 |
+
The following hyperparameters were used during training:
|
| 46 |
+
- learning_rate: 5e-05
|
| 47 |
+
- train_batch_size: 8
|
| 48 |
+
- eval_batch_size: 8
|
| 49 |
+
- seed: 42
|
| 50 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 51 |
+
- lr_scheduler_type: linear
|
| 52 |
+
- num_epochs: 10
|
| 53 |
+
|
| 54 |
+
### Training results
|
| 55 |
+
|
| 56 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 57 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 58 |
+
| No log | 1.0 | 71 | 0.1547 | 0.5048 | 0.3774 | 0.4319 | 0.9430 |
|
| 59 |
+
| No log | 2.0 | 142 | 0.1542 | 0.5965 | 0.4071 | 0.4839 | 0.9495 |
|
| 60 |
+
| No log | 3.0 | 213 | 0.1369 | 0.5519 | 0.5160 | 0.5334 | 0.9516 |
|
| 61 |
+
| No log | 4.0 | 284 | 0.1435 | 0.5622 | 0.4989 | 0.5287 | 0.9512 |
|
| 62 |
+
| No log | 5.0 | 355 | 0.1542 | 0.5920 | 0.5575 | 0.5742 | 0.9536 |
|
| 63 |
+
| No log | 6.0 | 426 | 0.1625 | 0.6069 | 0.5663 | 0.5859 | 0.9546 |
|
| 64 |
+
| No log | 7.0 | 497 | 0.1779 | 0.5936 | 0.5830 | 0.5883 | 0.9526 |
|
| 65 |
+
| 0.0978 | 8.0 | 568 | 0.1827 | 0.6035 | 0.5784 | 0.5907 | 0.9546 |
|
| 66 |
+
| 0.0978 | 9.0 | 639 | 0.2026 | 0.6121 | 0.5685 | 0.5895 | 0.9546 |
|
| 67 |
+
| 0.0978 | 10.0 | 710 | 0.2057 | 0.6288 | 0.5579 | 0.5912 | 0.9555 |
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
### Framework versions
|
| 71 |
+
|
| 72 |
+
- Transformers 4.34.0
|
| 73 |
+
- Pytorch 2.0.1+cu118
|
| 74 |
+
- Datasets 2.14.5
|
| 75 |
+
- Tokenizers 0.14.1
|