---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-dapt
  results: []
datasets:
- DerivedFunction/sec-filings-snippets
language:
- en
pipeline_tag: fill-mask
---

<!-- 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-dapt

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on a dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3623

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8489        | 0.1195 | 500  | 1.7333          |
| 1.6703        | 0.2390 | 1000 | 1.5837          |
| 1.5914        | 0.3585 | 1500 | 1.5023          |
| 1.5805        | 0.4780 | 2000 | 1.4578          |
| 1.5379        | 0.5975 | 2500 | 1.4236          |
| 1.4827        | 0.7170 | 3000 | 1.4011          |
| 1.4549        | 0.8365 | 3500 | 1.3739          |
| 1.4450        | 0.9560 | 4000 | 1.3623          |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.2