---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- source_data
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-cased-lora-finetuned-ner-EMBO-SourceData
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-large-cased-lora-finetuned-ner-EMBO-SourceData

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the source_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1282
- Precision: 0.7999
- Recall: 0.8278
- F1: 0.8136
- Accuracy: 0.9584

## 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: 0.001
- 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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1552        | 1.0   | 3454  | 0.1499          | 0.7569    | 0.7968 | 0.7763 | 0.9516   |
| 0.1179        | 2.0   | 6908  | 0.1328          | 0.7910    | 0.8120 | 0.8013 | 0.9564   |
| 0.0998        | 3.0   | 10362 | 0.1282          | 0.7999    | 0.8278 | 0.8136 | 0.9584   |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.13.3