metadata
license: apache-2.0
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: SetFit/distilbert-base-uncased__sst2__train-16-0
model-index:
- name: >-
SetFit_distilbert-base-uncased__sst2__train-16-0-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: 0.732620320855615
name: accuracy
SetFit_distilbert-base-uncased__sst2__train-16-0-finetuned-lora-tweet_eval_emotion
This model is a fine-tuned version of SetFit/distilbert-base-uncased__sst2__train-16-0 on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.7326
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 |
|---|---|---|
| 0.2380 | None | 0 |
| 0.6604 | 1.0387 | 0 |
| 0.7380 | 0.6947 | 1 |
| 0.7406 | 0.6149 | 2 |
| 0.7326 | 0.5885 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2