metadata
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: dhimskyy/wiki-bert
model-index:
- name: dhimskyy_wiki-bert-finetuned-lora-tweet_eval_hate
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
config: hate
split: validation
args: hate
metrics:
- type: accuracy
value: 0.677
name: accuracy
dhimskyy_wiki-bert-finetuned-lora-tweet_eval_hate
This model is a fine-tuned version of dhimskyy/wiki-bert on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.677
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 |
|---|---|---|
| 0.425 | None | 0 |
| 0.641 | 0.6638 | 0 |
| 0.672 | 0.5939 | 1 |
| 0.653 | 0.5487 | 2 |
| 0.677 | 0.5339 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2