--- library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: isakbos/Q8BERT_COLA_L_512 model-index: - name: isakbos_Q8BERT_COLA_L_512-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: 0.5717277486910994 name: accuracy --- # isakbos_Q8BERT_COLA_L_512-finetuned-lora-tweet_eval_irony This model is a fine-tuned version of [isakbos/Q8BERT_COLA_L_512](https://huggingface.co./isakbos/Q8BERT_COLA_L_512) on the tweet_eval dataset. It achieves the following results on the evaluation set: - accuracy: 0.5717 ## 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 | |:--------:|:----------:|:-----:| | 0.4775 | None | 0 | | 0.5225 | 0.6953 | 0 | | 0.5414 | 0.6890 | 1 | | 0.5518 | 0.6639 | 2 | | 0.5445 | 0.6554 | 3 | | 0.5508 | 0.6485 | 4 | | 0.5560 | 0.6457 | 5 | | 0.5560 | 0.6427 | 6 | | 0.5717 | 0.6385 | 7 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2