metadata
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: roberta-base-finetuned-mrpc
results: []
roberta-base-finetuned-mrpc
This model is a fine-tuned version of roberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2891
- Accuracy: 0.8925
- F1: 0.9228
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- training precision: Mixed Precision
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5998 | 1.0 | 57 | 0.5425 | 0.74 | 0.8349 |
| 0.5058 | 2.0 | 114 | 0.3020 | 0.875 | 0.9084 |
| 0.3316 | 3.0 | 171 | 0.2891 | 0.8925 | 0.9228 |
| 0.1617 | 4.0 | 228 | 0.2937 | 0.8825 | 0.9138 |
| 0.3161 | 5.0 | 285 | 0.3193 | 0.8875 | 0.9171 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.3.2
- Tokenizers 0.12.1