README.md

---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: IMDb_data_subset-MLM_with-custom_collator-distilbert-base-uncased
  results: []
language:
- en
---

# IMDb_data_subset-MLM_with-custom_collator-distilbert-base-uncased

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on IMDb dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2538
- Model Preparation Time: 0.0042

## Model description

[distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased)

## Intended uses & limitations

Mask filling

## Training and evaluation data

The IMDb dataset is tokenized, and words are masked with 0.2 probability. The resulting dataset is downsampled, resulting in 10,000 training samples and 1,000 validation samples.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|
| 3.5579        | 1.0   | 157  | 3.3058          | 0.0042                 |
| 3.3945        | 2.0   | 314  | 3.2732          | 0.0042                 |
| 3.3487        | 3.0   | 471  | 3.2542          | 0.0042                 |
| 3.3088        | 4.0   | 628  | 3.2237          | 0.0042                 |
| 3.2961        | 5.0   | 785  | 3.2538          | 0.0042                 |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1