File size: 1,345 Bytes
3da5e9f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
datasets:
- shipping_label_ner
model-index:
- name: ner_bert_model
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. -->
# ner_bert_model
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the shipping_label_ner dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1076
- eval_precision: 0.9091
- eval_recall: 0.9524
- eval_f1: 0.9302
- eval_accuracy: 0.9691
- eval_runtime: 0.325
- eval_samples_per_second: 15.384
- eval_steps_per_second: 9.23
- epoch: 13.0
- step: 130
## 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: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|