---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_0.0001_webDiscourse_01_03_2022-15_16_57
  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_token_itr0_0.0001_webDiscourse_01_03_2022-15_16_57

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5923
- Precision: 0.0039
- Recall: 0.0212
- F1: 0.0066
- Accuracy: 0.7084

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 10   | 0.6673          | 0.0476    | 0.0128 | 0.0202 | 0.6652   |
| No log        | 2.0   | 20   | 0.6211          | 0.0       | 0.0    | 0.0    | 0.6707   |
| No log        | 3.0   | 30   | 0.6880          | 0.0038    | 0.0128 | 0.0058 | 0.6703   |
| No log        | 4.0   | 40   | 0.6566          | 0.0030    | 0.0128 | 0.0049 | 0.6690   |
| No log        | 5.0   | 50   | 0.6036          | 0.0       | 0.0    | 0.0    | 0.6868   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3