metadata
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: philschmid/tiny-distilbert-classification
model-index:
- name: >-
philschmid_tiny-distilbert-classification-finetuned-lora-tweet_eval_offensive
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
config: offensive
split: validation
args: offensive
metrics:
- type: accuracy
value: 0.6533232628398792
name: accuracy
philschmid_tiny-distilbert-classification-finetuned-lora-tweet_eval_offensive
This model is a fine-tuned version of philschmid/tiny-distilbert-classification on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.6533
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: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| accuracy | train_loss | epoch |
|---|---|---|
| 0.6533 | None | 0 |
| 0.6533 | 0.6694 | 0 |
| 0.6533 | 0.6432 | 1 |
| 0.6533 | 0.6390 | 2 |
| 0.6533 | 0.6376 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2