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library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: fine_tune_distilbert-base-uncased
results: []
datasets:
- stanfordnlp/imdb
---
<!-- 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. -->
# fine_tune_distilbert-base-uncased
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: 2.1226
- Model Preparation Time: 0.0016
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|
| 2.5551 | 1.0 | 767 | 2.3648 | 0.0016 |
| 2.4329 | 2.0 | 1534 | 2.3181 | 0.0016 |
| 2.3874 | 3.0 | 2301 | 2.2831 | 0.0016 |
| 2.3409 | 4.0 | 3068 | 2.2422 | 0.0016 |
| 2.3124 | 5.0 | 3835 | 2.2302 | 0.0016 |
| 2.2895 | 6.0 | 4602 | 2.2104 | 0.0016 |
| 2.2649 | 7.0 | 5369 | 2.2014 | 0.0016 |
| 2.2445 | 8.0 | 6136 | 2.1939 | 0.0016 |
| 2.234 | 9.0 | 6903 | 2.1776 | 0.0016 |
| 2.2142 | 10.0 | 7670 | 2.1607 | 0.0016 |
| 2.208 | 11.0 | 8437 | 2.1682 | 0.0016 |
| 2.1933 | 12.0 | 9204 | 2.1530 | 0.0016 |
| 2.1808 | 13.0 | 9971 | 2.1493 | 0.0016 |
| 2.1689 | 14.0 | 10738 | 2.1422 | 0.0016 |
| 2.1598 | 15.0 | 11505 | 2.1347 | 0.0016 |
| 2.1567 | 16.0 | 12272 | 2.1373 | 0.0016 |
| 2.1458 | 17.0 | 13039 | 2.1270 | 0.0016 |
| 2.1475 | 18.0 | 13806 | 2.1200 | 0.0016 |
| 2.141 | 19.0 | 14573 | 2.1312 | 0.0016 |
| 2.1423 | 20.0 | 15340 | 2.1202 | 0.0016 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1 |