duynhatran's picture
End of training
722ecfb verified
|
raw
history blame
1.71 kB
---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta_textclassification
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. -->
# deberta_textclassification
This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3259
- Accuracy: 0.8781
- F1: 0.9135
## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 180 | 0.3881 | 0.8406 | 0.8889 |
| No log | 2.0 | 360 | 0.3333 | 0.8688 | 0.9079 |
| 0.4361 | 3.0 | 540 | 0.3758 | 0.8375 | 0.8802 |
| 0.4361 | 4.0 | 720 | 0.3378 | 0.8781 | 0.9147 |
| 0.4361 | 5.0 | 900 | 0.3259 | 0.8781 | 0.9135 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1