---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distil_train_token_classification_new
  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. -->

# distil_train_token_classification_new

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5252
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8077

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.5713        | 1.0   | 7361  | 0.5417          | 0.0       | 0.0    | 0.0 | 0.7846   |
| 0.4646        | 2.0   | 14722 | 0.5028          | 0.0       | 0.0    | 0.0 | 0.8014   |
| 0.4084        | 3.0   | 22083 | 0.5115          | 0.0       | 0.0    | 0.0 | 0.8077   |
| 0.3601        | 4.0   | 29444 | 0.5252          | 0.0       | 0.0    | 0.0 | 0.8077   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0