metadata
license: mit
tags:
- generated_from_trainer
datasets:
- stereoset
metrics:
- accuracy
model-index:
- name: stereoset_trainer_roberta-base_finetuned
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: stereoset
type: stereoset
config: intersentence
split: validation
args: intersentence
metrics:
- name: Accuracy
type: accuracy
value: 0.7535321821036107
stereoset_trainer_roberta-base_finetuned
This model is a fine-tuned version of roberta-base on the stereoset dataset. It achieves the following results on the evaluation set:
- Loss: 0.5749
- Accuracy: 0.7535
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: 5e-05
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.54 | 50 | 0.6919 | 0.5157 |
No log | 1.08 | 100 | 0.6944 | 0.4843 |
No log | 1.61 | 150 | 0.6275 | 0.6664 |
No log | 2.15 | 200 | 0.5548 | 0.7355 |
No log | 2.69 | 250 | 0.5613 | 0.7331 |
No log | 3.23 | 300 | 0.6062 | 0.7331 |
No log | 3.76 | 350 | 0.5455 | 0.7488 |
No log | 4.3 | 400 | 0.6223 | 0.7488 |
No log | 4.84 | 450 | 0.5749 | 0.7535 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1