| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: mt5-small-finetuned-imdb |
| 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. --> |
|
|
| # mt5-small-finetuned-imdb |
|
|
| 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: 2.4892 |
| - Model Preparation Time: 0.0022 |
|
|
| ## 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: 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 |
| - num_epochs: 3.0 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:| |
| | 2.6814 | 1.0 | 157 | 2.4930 | 0.0022 | |
| | 2.5825 | 2.0 | 314 | 2.4480 | 0.0022 | |
| | 2.5258 | 3.0 | 471 | 2.4823 | 0.0022 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.6 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 3.6.0 |
| - Tokenizers 0.22.2 |
| |
