|
--- |
|
license: mit |
|
base_model: xlm-roberta-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- fjd_dataset |
|
model-index: |
|
- name: xlmr-lstm-crf-resume-ner |
|
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. --> |
|
|
|
# xlmr-lstm-crf-resume-ner |
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the fjd_dataset dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 43.2243 |
|
- eval_precision: 0.4855 |
|
- eval_recall: 0.5854 |
|
- eval_f1: 0.5308 |
|
- eval_accuracy: 0.9488 |
|
- eval_runtime: 63.171 |
|
- eval_samples_per_second: 78.739 |
|
- eval_steps_per_second: 1.235 |
|
- epoch: 4.0 |
|
- step: 7360 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 100 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.1 |
|
|
