metadata
license: apache-2.0
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: emrecan/bert-base-multilingual-cased-snli_tr
model-index:
- name: >-
emrecan_bert-base-multilingual-cased-snli_tr-finetuned-lora-tweet_eval_irony
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
config: irony
split: validation
args: irony
metrics:
- type: accuracy
value: 0.6544502617801047
name: accuracy
emrecan_bert-base-multilingual-cased-snli_tr-finetuned-lora-tweet_eval_irony
This model is a fine-tuned version of emrecan/bert-base-multilingual-cased-snli_tr on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.6545
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: 0.0005
- 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: 8
Training results
| accuracy | train_loss | epoch |
|---|---|---|
| 0.4890 | None | 0 |
| 0.5832 | 0.6882 | 0 |
| 0.6010 | 0.6555 | 1 |
| 0.6073 | 0.6323 | 2 |
| 0.6304 | 0.6103 | 3 |
| 0.6377 | 0.5919 | 4 |
| 0.6419 | 0.5777 | 5 |
| 0.6492 | 0.5652 | 6 |
| 0.6545 | 0.5568 | 7 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2