---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert_finetuned_claimdecomp
  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_finetuned_claimdecomp

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: 9.3205
- Accuracy: 0.335

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0064        | 50.0  | 5000  | 5.7963          | 0.375    |
| 0.0           | 100.0 | 10000 | 7.2917          | 0.36     |
| 0.0           | 150.0 | 15000 | 7.0473          | 0.33     |
| 0.0           | 200.0 | 20000 | 8.0988          | 0.31     |
| 0.0           | 250.0 | 25000 | 8.8824          | 0.325    |
| 0.0           | 300.0 | 30000 | 9.3205          | 0.335    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1