metadata
license: mit
base_model: roberta-large
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-large
results: []
library_name: peft
datasets:
- AndersGiovanni/10-dim
language:
- en
pipeline_tag: text-classification
roberta-large
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2277
- Accuracy: 0.0883
- Precision: 0.6211
- Recall: 0.1909
- F1: 0.2920
- Hamming Loss: 0.1984
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
Framework versions
- PEFT 0.5.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2