metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta_large-chunking_0811_v7
results: []
roberta_large-chunking_0811_v7
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3687
- Precision: 0.8237
- Recall: 0.8406
- F1: 0.8320
- Accuracy: 0.9134
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1929 | 1.0 | 1249 | 0.4165 | 0.8034 | 0.8191 | 0.8112 | 0.9047 |
| 0.0789 | 2.0 | 2498 | 0.4161 | 0.8262 | 0.8363 | 0.8312 | 0.9088 |
| 0.0319 | 3.0 | 3747 | 0.5684 | 0.8104 | 0.8380 | 0.8240 | 0.9037 |
| 0.0198 | 4.0 | 4996 | 0.6959 | 0.8237 | 0.8433 | 0.8334 | 0.9067 |
| 0.0098 | 5.0 | 6245 | 0.7280 | 0.8234 | 0.8453 | 0.8342 | 0.9084 |
| 0.0075 | 6.0 | 7494 | 0.7482 | 0.8259 | 0.8482 | 0.8369 | 0.9075 |
| 0.0041 | 7.0 | 8743 | 0.7807 | 0.8396 | 0.8527 | 0.8461 | 0.9113 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1