metadata
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: ishan/bert-base-uncased-mnli
model-index:
- name: ishan_bert-base-uncased-mnli-finetuned-lora-tweet_eval_hate
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
config: hate
split: validation
args: hate
metrics:
- type: accuracy
value: 0.73
name: accuracy
ishan_bert-base-uncased-mnli-finetuned-lora-tweet_eval_hate
This model is a fine-tuned version of ishan/bert-base-uncased-mnli on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.73
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 |
|---|---|---|
| 0.511 | None | 0 |
| 0.715 | 0.5720 | 0 |
| 0.728 | 0.4651 | 1 |
| 0.719 | 0.4356 | 2 |
| 0.73 | 0.4258 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2