metadata
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
model-index:
- name: green_as_train_context_roberta-large
results: []
green_as_train_context_roberta-large
This model is a fine-tuned version of FacebookAI/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8427
- Accuracy: 0.8885
- Recall: 0.5802
- F1: 0.6533
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 |
---|---|---|---|---|---|---|
0.1927 | 1.0 | 1012 | 0.3691 | 0.8916 | 0.5864 | 0.6620 |
0.1417 | 2.0 | 2024 | 0.4204 | 0.8944 | 0.6281 | 0.6829 |
0.0954 | 3.0 | 3036 | 0.5585 | 0.8932 | 0.6111 | 0.6746 |
0.0447 | 4.0 | 4048 | 0.7888 | 0.8890 | 0.5849 | 0.6563 |
0.0217 | 5.0 | 5060 | 0.8427 | 0.8885 | 0.5802 | 0.6533 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2