license: mit | |
tags: | |
- generated_from_trainer | |
metrics: | |
- precision | |
- recall | |
- f1 | |
- accuracy | |
model-index: | |
- name: roberta-large-condaqa-neg-tag-token-classification-v2 | |
results: [] | |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
should probably proofread and complete it, then remove this comment. --> | |
# roberta-large-condaqa-neg-tag-token-classification-v2 | |
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.0336 | |
- Precision: 0.0 | |
- Recall: 0.0 | |
- F1: 0.0 | |
- Accuracy: 0.9916 | |
## 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: 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: 6.0 | |
### Training results | |
### Framework versions | |
- Transformers 4.25.0.dev0 | |
- Pytorch 1.10.1 | |
- Datasets 2.6.1 | |
- Tokenizers 0.13.1 | |