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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-tokenclassification_lora
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. -->
# distilbert-base-uncased-tokenclassification_lora
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3198
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9213
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log | 1.0 | 213 | 0.4745 | 0.0 | 0.0 | 0.0 | 0.9205 |
| No log | 2.0 | 426 | 0.4360 | 0.0 | 0.0 | 0.0 | 0.9205 |
| 0.8491 | 3.0 | 639 | 0.3983 | 0.0 | 0.0 | 0.0 | 0.9205 |
| 0.8491 | 4.0 | 852 | 0.3645 | 0.0 | 0.0 | 0.0 | 0.9205 |
| 0.2454 | 5.0 | 1065 | 0.3428 | 0.0 | 0.0 | 0.0 | 0.9205 |
| 0.2454 | 6.0 | 1278 | 0.3345 | 0.0 | 0.0 | 0.0 | 0.9208 |
| 0.2454 | 7.0 | 1491 | 0.3266 | 0.0 | 0.0 | 0.0 | 0.9208 |
| 0.2139 | 8.0 | 1704 | 0.3227 | 0.0 | 0.0 | 0.0 | 0.9210 |
| 0.2139 | 9.0 | 1917 | 0.3203 | 0.0 | 0.0 | 0.0 | 0.9212 |
| 0.2027 | 10.0 | 2130 | 0.3198 | 0.0 | 0.0 | 0.0 | 0.9213 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0 |