End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: mit
|
| 4 |
+
base_model: microsoft/deberta-v3-base
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
metrics:
|
| 8 |
+
- accuracy
|
| 9 |
+
- f1
|
| 10 |
+
model-index:
|
| 11 |
+
- name: deberta_Eau
|
| 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 |
+
# deberta_Eau
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.0898
|
| 23 |
+
- Accuracy: 0.9551
|
| 24 |
+
- F1: 0.9533
|
| 25 |
+
|
| 26 |
+
## Model description
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Intended uses & limitations
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training and evaluation data
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training procedure
|
| 39 |
+
|
| 40 |
+
### Training hyperparameters
|
| 41 |
+
|
| 42 |
+
The following hyperparameters were used during training:
|
| 43 |
+
- learning_rate: 5e-05
|
| 44 |
+
- train_batch_size: 32
|
| 45 |
+
- eval_batch_size: 32
|
| 46 |
+
- seed: 42
|
| 47 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
| 48 |
+
- lr_scheduler_type: linear
|
| 49 |
+
- num_epochs: 30
|
| 50 |
+
- mixed_precision_training: Native AMP
|
| 51 |
+
|
| 52 |
+
### Training results
|
| 53 |
+
|
| 54 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|
| 55 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
|
| 56 |
+
| 1.1053 | 1.0 | 67 | 0.4668 | 0.8652 | 0.8481 |
|
| 57 |
+
| 0.4887 | 2.0 | 134 | 0.2434 | 0.9220 | 0.9225 |
|
| 58 |
+
| 0.2714 | 3.0 | 201 | 0.2129 | 0.9333 | 0.9341 |
|
| 59 |
+
| 0.2296 | 4.0 | 268 | 0.1752 | 0.9319 | 0.9341 |
|
| 60 |
+
| 0.2098 | 5.0 | 335 | 0.1676 | 0.9418 | 0.9402 |
|
| 61 |
+
| 0.1881 | 6.0 | 402 | 0.1473 | 0.9433 | 0.9443 |
|
| 62 |
+
| 0.1472 | 7.0 | 469 | 0.0982 | 0.9504 | 0.9515 |
|
| 63 |
+
| 0.1332 | 8.0 | 536 | 0.0969 | 0.9527 | 0.9517 |
|
| 64 |
+
| 0.1291 | 9.0 | 603 | 0.0919 | 0.9537 | 0.9517 |
|
| 65 |
+
| 0.1146 | 10.0 | 670 | 0.0898 | 0.9551 | 0.9533 |
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
### Framework versions
|
| 69 |
+
|
| 70 |
+
- Transformers 4.48.3
|
| 71 |
+
- Pytorch 2.5.1+cu124
|
| 72 |
+
- Datasets 3.3.2
|
| 73 |
+
- Tokenizers 0.21.0
|