metadata
library_name: peft
tags:
- parquet
- text-classification
datasets:
- ag_news
metrics:
- accuracy
base_model: manueltonneau/bert-twitter-en-is-hired
model-index:
- name: manueltonneau_bert-twitter-en-is-hired-finetuned-lora-ag_news
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: ag_news
type: ag_news
config: default
split: test
args: default
metrics:
- type: accuracy
value: 0.9278947368421052
name: accuracy
manueltonneau_bert-twitter-en-is-hired-finetuned-lora-ag_news
This model is a fine-tuned version of manueltonneau/bert-twitter-en-is-hired on the ag_news dataset. It achieves the following results on the evaluation set:
- accuracy: 0.9279
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: 24
- eval_batch_size: 24
- 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 |
|---|---|---|
| 0.2579 | None | 0 |
| 0.915 | 0.3467 | 0 |
| 0.9212 | 0.2345 | 1 |
| 0.9272 | 0.2132 | 2 |
| 0.9279 | 0.2009 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2