metadata

license: apache-2.0
library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - rotten_tomatoes
metrics:
  - accuracy
base_model: Alassea/glue_sst_classifier
model-index:
  - name: Alassea_glue_sst_classifier-finetuned-lora-rotten_tomatoes
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: rotten_tomatoes
          type: rotten_tomatoes
          config: default
          split: validation
          args: default
        metrics:
          - type: accuracy
            value: 0.8808630393996247
            name: accuracy

Alassea_glue_sst_classifier-finetuned-lora-rotten_tomatoes

This model is a fine-tuned version of Alassea/glue_sst_classifier on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:

accuracy: 0.8809

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
0.8724	None	0
0.8715	0.3353	0
0.8724	0.3133	1
0.8799	0.3031	2
0.8809	0.2947	3

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2