vedica1011's picture
vedica1011/distilbert-base-uncased-lora-text-classification
8b564ea
|
raw
history blame
2.14 kB
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-lora-text-classification
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. -->
# distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9997
- Accuracy: {'accuracy': 0.882}
## 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: 0.001
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|
| No log | 1.0 | 250 | 0.3444 | {'accuracy': 0.888} |
| 0.4135 | 2.0 | 500 | 0.4854 | {'accuracy': 0.887} |
| 0.4135 | 3.0 | 750 | 0.6411 | {'accuracy': 0.882} |
| 0.2383 | 4.0 | 1000 | 0.6366 | {'accuracy': 0.891} |
| 0.2383 | 5.0 | 1250 | 0.7062 | {'accuracy': 0.891} |
| 0.1144 | 6.0 | 1500 | 0.7646 | {'accuracy': 0.882} |
| 0.1144 | 7.0 | 1750 | 0.9373 | {'accuracy': 0.884} |
| 0.0176 | 8.0 | 2000 | 1.0347 | {'accuracy': 0.884} |
| 0.0176 | 9.0 | 2250 | 0.9923 | {'accuracy': 0.883} |
| 0.0188 | 10.0 | 2500 | 0.9997 | {'accuracy': 0.882} |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1