README.md

metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - tweet_eval
metrics:
  - accuracy
base_model: aviator-neural/bert-base-uncased-sst2
model-index:
  - name: aviator-neural_bert-base-uncased-sst2-finetuned-lora-tweet_eval_emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: emotion
          split: validation
          args: emotion
        metrics:
          - type: accuracy
            value: 0.5935828877005348
            name: accuracy

aviator-neural_bert-base-uncased-sst2-finetuned-lora-tweet_eval_emotion

This model is a fine-tuned version of aviator-neural/bert-base-uncased-sst2 on the tweet_eval dataset. It achieves the following results on the evaluation set:

• accuracy: 0.5936

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
0.1791	None	0
0.5588	1.1340	0
0.5775	1.0738	1
0.5829	1.0354	2
0.5936	1.0207	3

Framework versions

• PEFT 0.8.2
• Transformers 4.37.2
• Pytorch 2.2.0
• Datasets 2.16.1
• Tokenizers 0.15.2